Update README.md

README.md

@@ -25,13 +25,13 @@ widget:
 
 ## Model description
 
-Cased fine-tuned XLM-RoBERTa-large model for Hungarian, trained to classify sentences based on their plain language comprehensibility.
+Cased fine-tuned XLM-RoBERTa-large model for Hungarian, trained to classify **sentences** based on their Plain Language properties.
 
 ## Intended uses & limitations
 
 The model is designed to classify sentences as either "comprehensible" or "not comprehensible" (according to Plain Language guidelines):
-* **Label_0** - "comprehensible"
-* **Label_1** - "not comprehensible"
+* **Label_0** - "comprehensible" - The sentence is in Plain Language.
+* **Label_1** - "not comprehensible" - The sentence is **not** in Plain Language.
 
 ## Training
 
@@ -54,4 +54,12 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
 tokenizer = AutoTokenizer.from_pretrained("uvegesistvan/Hun_RoBERTa_large_Plain")
 model = AutoModelForSequenceClassification.from_pretrained("uvegesistvan/Hun_RoBERTa_large_Plain")
-```
+```
+
+# Citation:
+@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}
+}