Update app.py

app.py

@@ -15,9 +15,9 @@ df.dropna(inplace=True)
 
 m = NeuralProphet(
     n_forecasts=30,
-    n_lags=7,
-    changepoints_range=1.1,
-    num_hidden_layers=6,
+    n_lags=30,
+    changepoints_range=1.3,
+    num_hidden_layers=3,
     daily_seasonality=False,
     weekly_seasonality=True,
     yearly_seasonality=True,
@@ -29,7 +29,7 @@ m = NeuralProphet(
     unknown_data_normalization=True,
     seasonality_mode="multiplicative",
     drop_missing=True,
-    learning_rate=0.07
+    learning_rate=0.1
 )
 
 m.fit(df, freq='D')