Use eval() from keras.backend:
import keras.backend as K
from keras.models import Sequential
from keras.layers import Dense
model = Sequential()
model.add(Dense(1, input_shape=(1,)))
model.add(Dense(1))
model.compile(loss="mse", optimizer="adam")
print(K.eval(model.optimizer.lr))
Output:
0.001