Update README.md

README.md

@@ -128,7 +128,7 @@ The model is designed to predict safety labels across the following categories:
 - **Model type:** Transformer Encoder
 - **Language(s) (NLP):** Thai 🇹🇭 and English 🇬🇧
 - **License:** MIT
-- **Finetuned from model [optional]:** mDeBERTa v3 base https://huggingface.co/microsoft/mdeberta-v3-base
+- **Finetuned from model:** mDeBERTa v3 base https://huggingface.co/microsoft/mdeberta-v3-base
 
 
 ## How to Get Started with the Model
@@ -162,7 +162,7 @@ labels = predictions.argmax(dim=1).tolist()
 scores = predictions.max(dim=1).values.tolist()
 
 # Define label mapping
-label_map = {0: "Unharm", 1: "harmful"}
+label_map = {0: "Unharm", 1: "Harmful"}
 
 for text, label, score in zip(texts, labels, scores):
     label_name = label_map[label]