Plot losses
Once we've fit a model, we usually check the training loss curve to make sure it's flattened out. The history
returned from model.fit()
is a dictionary that has an entry, 'loss'
, which is the training loss. We want to ensure this has more or less flattened out at the end of our training.
Cet exercice fait partie du cours
Machine Learning for Finance in Python
Instructions
- Plot the losses (
'loss'
) fromhistory.history
. - Set the title of the plot as the last loss from
history.history
, and round it to 6 digits.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Plot the losses from the fit
plt.plot(____)
# Use the last loss as the title
plt.title('loss:' + str(round(____, 6)))
plt.show()