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---
license: cc-by-nc-4.0
language:
- hu
metrics:
- accuracy
- f1
model-index:
- name: Hun_RoBERTa_large_Plain
results:
- task:
type: text-classification
metrics:
- type: accuracy
value: 0.72
- type: f1
value: 0.72
widget:
- text: "A tanúsítvány meghatározott adatainak a 2008/118/EK irányelv IV. fejezete szerinti szállításához szükséges adminisztratív okmányban..."
example_title: "Incomprehensible"
- text: "Az AEO-engedély birtokosainak listáján – keresésre – megjelenő információk: az engedélyes neve, az engedélyt kibocsátó ország..."
example_title: "Comprehensible"
---
## Model description
Cased fine-tuned XLM-RoBERTa-large model for Hungarian, trained on a dataset (~13k sentences) provided by National Tax and Customs Administration - Hungary (NAV): Public Accessibilty Programme.
## Intended uses & limitations
The model is designed to classify sentences as either "comprehensible" or "not comprehensible" (according to Plain Language guidelines):
* **Label_0** - "comprehensible" - The sentence is in Plain Language.
* **Label_1** - "not comprehensible" - The sentence is **not** in Plain Language.
## Training
Fine-tuned version of the original `xlm-roberta-large` model, trained on a dataset of Hungarian legal and administrative texts.
## Eval results
| Class | Precision | Recall | F-Score |
| ----- | --------- | ------ | ------- |
| **Comprehensible / Label_0** | **0.74** | **0.65** | **0.70** |
| **Not comprehensible / Label_1** | **0.71** | **0.79** | **0.74** |
| **accuracy** | | | **0.72** |
| **macro avg** | **0.73** | **0.72** | **0.72** |
| **weighted avg** | **0.72** | **0.72** | **0.72** |
## Usage
```py
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("uvegesistvan/Hun_RoBERTa_large_Plain")
model = AutoModelForSequenceClassification.from_pretrained("uvegesistvan/Hun_RoBERTa_large_Plain")
```
# Citation
Bibtex:
```bibtex
@PhDThesis{ Uveges:2024,
author = {{"U}veges, Istv{\'a}n},
title = {K{\"o}z{\'e}rthet{\"o} és automatiz{\'a}ci{\'o} - k{\'i}s{\'e}rletek a jog, term{\'e}szetesnyelv-feldolgoz{\'a}s {\'e}s informatika hat{\'a}r{\'a}n.},
year = {2024},
school = {Szegedi Tudom{\'a}nyegyetem}
}
``` |