Deep Learning Workshop

@@ -195,9 +195,10 @@ if __name__ == "__main__":
     history = model.fit(train_features, train_labels,
                         epochs=50, verbose=0, validation_split=0.25)
 
-    # Print model metrics
-    print("Model metics:")
-    print("\n\t%s:" % (model.metrics_names[1]))
+    # Print training metrics
+    print("Training metrics:")
+    model.evaluate(train_features, train_labels)
+    print("\n%s:" % (model.metrics_names[1]))
 
     # Plot training-validation loss
     plt.figure()
@@ -223,6 +224,12 @@ if __name__ == "__main__":
 
     # Predict with rest data set
     predicted_labels = model.predict(np.stack(test_features))
+
+    # Print test metrics
+    print("Test metrics:")
+    model.evaluate(train_features, train_labels)
+    print("\n%s:" % (model.metrics_names[1]))
+
     # Print confusion matrix
     cm = confusion_matrix(np.argmax(test_labels, axis=1),
                           np.argmax(predicted_labels, axis=1))