Update app.py

app.py

@@ -157,8 +157,11 @@ def predict_cognitive_state(sentence):
 title = "🧠 Cognitive State Analysis from Text"
 description = (
     "Enter a sentence to predict its cognitive state. This demo uses a fine-tuned BERT model for semantic "
-    "embeddings combined with 19 discrete linguistic features, fed into a Multi-Layer Perceptron (MLP) "
-    "to classify text as either 'Normal Reading (NR)' or 'Task-Specific Reading (TSR)' based on the ZuCo dataset."
+    "embeddings combined with 19 discrete linguistic features. These features are fed into a Multi-Layer Perceptron (MLP) "
+    "to classify the input as either:\n\n"
+    "- **Normal Reading (NR):** Casual reading without a specific goal—like reading a story or browsing news.\n"
+    "- **Task-Specific Reading (TSR):** Purpose-driven reading—such as searching for an answer or following instructions.\n\n"
+    "The model is trained on text data from the ZuCo dataset, using only linguistic features—no EEG or eye-tracking signals are used."
 )
 example_list = [
     ["Through his son Timothy Bush, Jr., who was also a blacksmith, descended two American Presidents -George H. W. Bush and George W. Bush."],