Evaluation Metrics
Metrics are calculated for each round of training
When the session is complete, you can see a set of metrics for all rounds of training, as well as metrics for the final model.
Retrieve Metrics for a Session
Use the SessionMetrics
class of the API to store and retrieve metrics for a session. You can retrieve the model performance metrics as a dictionary (Dict
), or plot them. See the API class reference for details.
Typical usage example:
Authenticate to and connect to the integrate.ai client.
Provide the session ID that you want to retrieve the metrics for as the
already_trained_session_id
.Call the
SessionMetrics
class.
Available Metrics
The Federated Loss value for the latest round of model training is reported as the global_model_federated_loss
(float) attribute for an instance of SessionMetrics.
This is a model level metric reported for each round of training. It is a weighted average loss across different clients, weighted by the number of examples/samples from each silo.
See the metrics by machine learning task in the following table:
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