Error updating hyperparameters in "Best so far"

[senyang1107]

Hello, I found a hyperparameter error in the Best so far after using randomsearch. As you can see from the picture, when the num_layers = 11 in Best so far, we should expect unit_11=none, but the opposite is true. I don't know why this problem has occurred, and I really hope to get your help.
The relevant codes are as follows:
def build_model(hp):
model = keras.Sequential()
for i in range(hp.Int('num_layers', 1, 12)):
#model.add(layers.Dense(units=hp.Choice('units_' + str(i), values=[4,8,16,32,64,128,256,512]), activation='relu'))
model.add(layers.Dense(units=hp.Int('units_' + str(i), min_value=16,max_value=512,step=16), activation='relu'))
model.add(Dropout(rate=hp.Float('dropout_rate', min_value=0.0, max_value=0.5, step=0.1)))
batch_size = hp.Int('batch_size', min_value=4, max_value=64, step=4) #
model.add(Dense(1,kernel_initializer=initializer)) #
model.compile(optimizer='adam', loss='mean_squared_error', metrics=[keras.metrics.RootMeanSquaredError()])
return model

tuner_RandomSearch = inner_cv(RandomSearch)(
build_model,
KFold(n_splits=10, random_state=2024, shuffle=True),
save_output=True,
save_history=True,
objective=keras_tuner.Objective("val_root_mean_squared_error", direction="min"),
directory='DNN240503',
project_name='randomsearch_Int_L1_112',
seed=2024,
max_trials=100,
overwrite=True,
allow_new_entries=True,
)
my_callbacks = [
keras.callbacks.EarlyStopping(monitor='val_root_mean_squared_error',
patience=10, restore_best_weights=True)
]
tuner_RandomSearch.search(
train_validation_X.values,
train_validation_Y.values,
validation_split=0.25,
epochs=500,
callbacks=[my_callbacks],
verbose=True)