The negative log likelihood (NLL) can be used both as a loss function to minimize during training as well as a metric to evaluate the model fitness. When calculating likelihood one assumes the predicted variances (σ 2 i ) to describe a Gaussian distribution of errors and multiplies the value of the probability distribution function for the observed errors (ε i ). The average NLL for the test set is then: