What metric does `Scalar test loss` in AutoKeras mean? I'm using the following code:

import autokeras as ak

regressor = ak.StructuredDataRegressor(max_trials=100)
regressor.fit(x=train_dataset.drop(columns=['MPG']), y=train_dataset['MPG'])
# Evaluate the accuracy of the found model.
print('Accuracy: {accuracy}'.format(
    accuracy=regressor.evaluate(x=test_dataset.drop(columns=['MPG']), y=test_dataset['MPG'])))


The result of the evaluate function is Scalar test loss. I just want to clarify what metric would that be. What is the default loss function?
Since you are using StructuredDataRegressor, the default loss function is mean squared error. That information can be found in the __init__ function with the default keyword argument `loss='mean_squared_error'.