Graph both loss and accuracy

1 files changed, 3 insertions, 2 deletions

diff --git a/lenet.py b/lenet.py
index 2372857..31664ee 100644
--- a/lenet.py
+++ b/lenet.py
@@ -116,7 +116,8 @@ def train_classifier(x_train, y_train, x_val, y_val, batch_size=128, epochs=100,
   model.compile(loss='categorical_crossentropy', metrics=metrics, optimizer=optimizer)
   
   history = model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, verbose=1, validation_data = (x_val, y_val))
-  plot_history(history, metrics)
+  plot_history(history, 'categorical_accuracy')
+  plot_history(history)
   return model 
 
 def test_classifier(model, x_test, y_true):
@@ -157,5 +158,5 @@ def mix_data(X_train, y_train, X_validation, y_validation, train_gen, tr_labels_
 if __name__ == '__main__':
   x_train, y_train, x_val, y_val, x_t, y_t = import_mnist()
   print(y_t.shape)
-  model = train_classifier(x_train[:100], y_train[:100], x_val, y_val, epochs=1)
+  model = train_classifier(x_train[:100], y_train[:100], x_val, y_val, epochs=3)
   test_classifier(model, x_t, y_t)