Update README.md

README.md

@@ -1,3 +1,54 @@
 ---
 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}
+}
+```