Metrics¶
A metric is a function that is used to judge the performance of your model. Metric functions are to be supplied to
the olympic.fit()
function at training time.
A metric function is similar to a loss function, except that the results from evaluating a metric are not used when training the model.
You can either pass the name of an existing metric, or pass a PyTorch function.
Custom Metrics¶
Custom metrics can also be passed to olympic.fit
. Custom metrics must take (y_true, y_pred)
as arguments and
return a single float as output. You should be able to pass any PyTorch loss function as a custom metric.