# 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](https://s3.ca-central-1.amazonaws.com/public.s3.integrate.ai/integrate_ai_sdk/0.3.5/docs/integrate_ai_sdk/api/session_metrics.html) for details. 

Typical usage example:

```python
client = connect("token") 

already_trained_session_id = "<sessionID>"

session = client.fl_session(already_trained_session_id)

# retrieve the metrics for the session as a dictionary
metrics = session.metrics.as_dict()
```

1. Authenticate to and connect to the integrate.ai client.
2. Provide the session ID that you want to retrieve the metrics for as the `already_trained_session_id``.
3. 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:

| Classification and Logistic | Regression and Normal, Tweedie (power = 0) | Poisson, Gamma, Tweedie (power > 0), Inverse Gaussian |
|---|---|---|
| [Loss (cross-entropy)](https://scikit-learn.org/stable/modules/model_evaluation.html#log-loss) | [Loss (mean squared score)](https://scikit-learn.org/stable/modules/model_evaluation.html#mean-squared-error) | [Loss (unit deviance)](https://scikit-learn.org/stable/modules/linear_model.html#generalized-linear-regression) |
| [ROC_AUC](https://scikit-learn.org/stable/modules/model_evaluation.html#receiver-operating-characteristic-roc) | [R2 score](https://scikit-learn.org/stable/modules/model_evaluation.html#r2-score-the-coefficient-of-determination) | [R2 score](https://scikit-learn.org/stable/modules/model_evaluation.html#r2-score-the-coefficient-of-determination) |
| [Accuracy](https://scikit-learn.org/stable/modules/model_evaluation.html#accuracy-score) || |