Update README.md

README.md

@@ -18,7 +18,7 @@ The Token-Level Bias Classifier is a transformer-based model developed to detect
 
 ## Model Architecture
 
-The model is built using the `distilbert-base-uncased` pretrained model, a smaller and faster version of BERT. It is fine-tuned on a custom dataset for the task of token-level bias classification. The model uses a Token Classification architecture, typically used for Named Entity Recognition (NER) tasks.
+The model is built using the pretrained model. It is fine-tuned on a custom dataset for the task of sentence-level bias classification. The model uses a Sentence Classification architecture, typically used for Text Classification tasks.
 
 ## Model Performance