Why does loss decrease but accuracy remain unchanged in Keras training?

Loss is continuous while accuracy is discrete, so improvements may not reflect in accuracy.

Loss captures probability confidence, while accuracy only measures thresholded correctness. Small probability improvements may not change predicted class.