I add a callback to decay learning rate:
keras.callbacks.ReduceLROnPlateau(monitor=\'val_loss\', factor=0.5, patience=100,
v
You gave the optimizer's code twice, instead of TensorBoard Callback. Anyway, I didn`t find the way to display the learning rate on TensorBoard. I am plotting it after the training finished, taking data from History object:
nb_epoch = len(history1.history['loss'])
learning_rate=history1.history['lr']
xc=range(nb_epoch)
plt.figure(3,figsize=(7,5))
plt.plot(xc,learning_rate)
plt.xlabel('num of Epochs')
plt.ylabel('learning rate')
plt.title('Learning rate')
plt.grid(True)
plt.style.use(['seaborn-ticks'])
The chart looks like this: LR plot
Sorry, that is not exactly what you are asking about, but perhaps could help.