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Since you're using categorical cross-entropy loss, the last layer (output layer) should come with softmax activation instead of identity (as being blank in layers.Dense(4)). model = tf.keras.Sequential([ normalize, ..., layers.Dense(4, activation=tf.keras.activations.softmax) ]) And SparseCategoricalCrossentropy is different from ...


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