Update app.py

app.py

@@ -10,7 +10,7 @@ with col1:
     st.markdown("Message spam detection tool for Turkish language. Due the small size of the dataset, I decided to go with transformers         technology Google BERT. Using the Turkish pre-trained model BERTurk, I imporved the accuracy of the tool by 18 percent compared to the previous model which used fastText.")
 
 with col2:
-    st.title("Spamd: Turkish Spam Detector")
+    st.title("Model:")
     if st.button('Load Model'):   
         with st.spinner('Wait for it...'):
             
@@ -66,13 +66,11 @@ with col2:
             
                 prediction = 'Spam' if np.argmax(output.logits.cpu().numpy()).flatten().item() == 1 else 'Normal'
                 pred = 'Predicted Class: '+ prediction
-                with col2:
-                    st.header(pred)
                 
-                #st.write('Input', namestr(new_sentence, globals()),': \n', new_sentence) 
-                with col2:
-                    text = st.text_input("Enter the text you'd like to analyze for spam.")
-                    if text or st.button('Analyze'):
-                        predict(text)
         st.success("Model Loaded!")
-    
+        
+with col2:
+    st.header(pred)
+    text = st.text_input("Enter the text you'd like to analyze for spam.")
+    if text or st.button('Analyze'):
+        predict(text)