Bug: "Best val_accuracy So Far" is mistaken for "Best val_loss So Far"

[baolongnguyenmac]

Bug Description

When I changed the objective from val_loss to val_accuracy, the value of "Best val_accuracy So Far" was wrong.
It displayed the maximum value of loss (only those which were smaller than 1)

# metrics was extracted from file `trial.json`
val_loss = np.array(metrics['list_val_loss'])
max(val_loss[val_loss < 1])

Bug Reproduction

You can try fitting the model with objective='val_loss', then stop the training process and change the objective to val_accuracy and the bug will appear.

I think that any data can be used to re-produce this error.

Expected Behavior

It should print out the accuracy instead of the loss value

Setup Details

Include the details about the versions of:

• OS type and version: Ubuntu 20.04.2 LTS
• Python: 3.11.8
• autokeras: 2.0.0
• keras-tuner: 1.4.7
• scikit-learn: 1.4.1.post1
• numpy: 1.26.4
• pandas: 2.2.1
• tensorflow: 2.16.1