Update app.py

app.py

@@ -29,9 +29,6 @@ with gr.Blocks() as demo:
 
         predictions = model(x_train[:1]).numpy()
         
-        print("TensorFlow version:", tf.__version__)
-        print(predictions)
-        
         tf.nn.softmax(predictions).numpy()
         
         loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
@@ -43,9 +40,9 @@ with gr.Blocks() as demo:
         
         
         model.fit(x_train, y_train, epochs=5)
-        model.evaluate(x_test,  y_test, verbose=2)
+        model_eval_data = model.evaluate(x_test,  y_test, verbose=2)
 
-        return "done"
+        return model_eval_data
         
 
     # Creates the Gradio interface objects