--- 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} } ```