# Why are the ANN training and validation accuracy graphs not smooth?

I am currently training an ANN using Keras (Python3), and I am slowly optimizing the model's architecture and came across something I have not seen before.

The graph of the training and validation accuracy seems a bit odd. The graph appears 'step-like' in the sense that it is not a smooth curve, but different.

Model:

model = tf.keras.models.Sequential()

loss='binary_crossentropy',
metrics=['accuracy', 'mse', 'mae'])

history = model.fit(
X_train.values,
y_train,
epochs=1000,
validation_split = 0.2,
verbose=1,
)


My two questions are:

(1) what is this indicative of, and

(2) how do i fix this assuming it is problematic?