Update app.py

app.py

@@ -72,9 +72,9 @@ except ValueError as e:
     X_train_resampled, y_train_resampled = X_train_tfidf, y_train
 
 # Logistic Regression Model
-# max iter exceeding 500 doesnt improve anything
-# Don't set C low, set to 100+ default. Tried for 200
-model = LogisticRegression(C=200, max_iter=200, n_jobs=-1, solver='lbfgs', multi_class='multinomial')
+# max iter exceeding 200 doesnt improve anything
+# Don't set C low, set to 100+ default. 200 works better.
+model = LogisticRegression(C=1000, max_iter=200, n_jobs=-1, solver='lbfgs', multi_class='multinomial')
 model.fit(X_train_resampled, y_train_resampled)
 
 # Evaluate Model
@@ -165,6 +165,7 @@ def analyze_tone(text, selected_tone=None):
 # Gradio interface Creation
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
     gr.Markdown("# Text Tone Sentimental Analyzer")
+    gr.Markdown("Be mindful of punctuation as it affects results. Slang is unaccounted for due to dataset constraints.")
     
     with gr.Row():
         with gr.Column(scale=3):
@@ -176,12 +177,13 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
             analyze_button = gr.Button("Analyze Tone", variant="primary")
             
         with gr.Column(scale=2):
-            # Example Tones Dropdown
             tone_dropdown = gr.Dropdown(
                 choices=sorted(df['label'].unique().tolist()),
                 label="Select a tone to view an example below."
             )
-    
+
+    gr.Markdown("<br>", elem_id="line-break-1")
+
     with gr.Row():
         with gr.Column(scale=1):
             result_message = gr.Markdown()
@@ -189,22 +191,22 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
     with gr.Row():
         with gr.Column(scale=2):
             plot_output = gr.Plot(label="Tone Probabilities")
-        with gr.Column(scale=1):
-            all_probs_output = gr.JSON(label="All Probabilities")
-            
+
     with gr.Row():
         examples_output = gr.Dataframe(
             headers=["Examples of similar texts"],
             datatype=["str"],
             label="Example texts with similar tone"
         )
-    
+
+    # Button callback
     analyze_button.click(
         fn=analyze_tone,
         inputs=[text_input, tone_dropdown],  
-        outputs=[result_message, all_probs_output, plot_output, examples_output]
+        outputs=[result_message, plot_output, examples_output]
     )
     
+    # Dropdown change
     tone_dropdown.change(
         fn=get_tone_examples,
         inputs=tone_dropdown,