why is sparsecategoricalcrossentropy not working with this machine learning model?

Assuming the labels are integers, they have the wrong shape for SparseCategoricalCrossentropy. Check the docs. Try converting your y to one-hot encoded labels:

y = tf.keras.utils.to_categorical(y, num_classes=20)

and change your loss function to CategoricalCrossentropy:

model.compile(optimizer=Nadam(lr=0.09), loss=tf.keras.losses.CategoricalCrossentropy(),
              metrics=['accuracy', mean_squared_error, mean_absolute_error, mean_absolute_percentage_error])

and it should work.