Update app.py

app.py

@@ -16,7 +16,7 @@ def spam_detection(message):
     prediction = model.predict(padded_sequence)[0, 0]
     
     # Return the result
-    return "Spam" if prediction >= 0.5 else "Not Spam"
+    return "Spam" if prediction >= 0.4 else "Not Spam"
 
 # Gradio Interface
 ui = gr.Interface(
@@ -24,7 +24,6 @@ ui = gr.Interface(
     inputs=gr.Textbox(label="Enter a message:",info='Check spam or not spam msg',lines=5),
     outputs="text",
     live=True,
-    theme="huggingface",
     title='🚫 Spam Message Detection 🕵️‍♂️',
     description="""
     Welcome to the Spam Message Detection app—a powerful demo designed for learning purposes. 🎓 This application employs advanced machine learning techniques to identify and flag spam messages with remarkable accuracy. 🤖 With a training set accuracy of 99.89% and a validation/test set accuracy of 98.39%, the model has been fine-tuned using a comprehensive dataset.
@@ -41,6 +40,7 @@ ui = gr.Interface(
     3. Receive instant feedback on whether the input message is classified as spam or not.
 
     **📌 Note: **
+    
     This app is a demonstration and educational tool. It showcases the effectiveness of machine learning in identifying spam messages. Enjoy exploring the world of spam detection with our highly accurate model! 🚀"""
 )
 # Launch the app