Update app.py

app.py

@@ -13,11 +13,11 @@ model = tf.keras.Sequential([
     tf.keras.layers.Dense(units=1, input_shape=[1])
 ])
 
-# Sidebar for hyperparameter tuning
-learning_rate = st.sidebar.slider('Learning Rate', 0.001, 0.1, 0.01)
-epochs = st.sidebar.slider('Epochs', 100, 1000, 500)
+# Set a suitable learning rate and number of epochs
+learning_rate = 0.01
+epochs = 500
 
-# Compile the model with selected optimizer and loss function
+# Compile the model with the selected optimizer and loss function
 optimizer = tf.keras.optimizers.SGD(learning_rate=learning_rate)
 model.compile(optimizer=optimizer, loss='mse')
 
@@ -31,7 +31,7 @@ input_celsius = st.number_input('Enter Celsius value:', value=0.0, format="%.1f"
 # Button to train the model and make prediction
 if st.button('Train Model and Predict Fahrenheit'):
     with st.spinner('Training...'):
-        # Fit the model with the user-defined hyperparameters
+        # Fit the model with hardcoded hyperparameters
         model.fit(celsius, fahrenheit, epochs=epochs)
     st.success('Training completed!')