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---
license: cc-by-nc-4.0
language:
- hu
metrics:
- accuracy
model-index:
- name: huBERTPlain
results:
- task:
type: text-classification
metrics:
- type: accuracy
value: 0.73
---
## Model description
Cased fine-tuned BERT model for Hungarian, trained on a dataset provided by National Tax and Customs Administration - Hungary (NAV): Public Accessibilty Programme.
## Intended uses & limitations
The model can be used as any other (cased) BERT model. It has been tested recognizing "accessible" and "original" sentences, where:
* "accessible" - "Label_1": sentence, that can be considered as comprehensible (regarding to Plain Language directives)
* "original" - "Label_0": sentence, that needs to rephrased in order to follow Plain Language Guidelines.
## Training
Fine-tuned version of the original huBERT model (`SZTAKI-HLT/hubert-base-cc`), trained on information materials provided by NAV linguistic experts.
## Eval results
| Class | Precision | Recall | F-Score |
|-----|------------|------------|------|
| **Original / Label_0** | **0.71** | **0.79** | **0.75**|
| **Accessible / Label_1** | **0.76** | **0.67** | **0.71**|
| **accuracy** | | | **0.73**|
| **macro avg** | **0.74** | **0.73** | **0.73**|
| **weighted avg** | **0.74** | **0.73** | **0.73**|
### BibTeX entry and citation info
If you use the model, please cite the following papers:
Bibtex:
```bibtex
@PhDThesis{ Uveges:2023,
author = {{"U}veges, Istv{\'a}n},
title = {A k{\"o}z{\'e}rthet{\"o}s{\'e}g lehet{\"o}s{\'e}gei a jogi dom{\'e}n sz{\"o}vegeiben},
year = {2023},
school = {Szegedi Tudom\'anyegyetem}
}
``` |