Machine Learning with Swift

Plotting loss

Loss values on training and validation sets allows to see, how our model improves over the time and decide when to stop training:

from matplotlib import pyplot as plt 
history.history.keys() 
['acc', 'loss', 'val_acc', 'val_loss'] plt.plot(history.history['loss']) 
plt.plot(history.history['val_loss']) 
plt.title('model loss') 
plt.ylabel('loss') 
plt.xlabel('epoch') 
plt.legend(['train', 'test'], loc='upper left') 
plt.show() 

Figure 9.11: Loss on training and test sets over the training epochs