I would like to use a hyperparameter search algorithm to find the best hyperparameters (L1 and L2). For this I think the last loss value reported by the training algorithm can be useful.
Is there a way to get the last loss value computed during training?
Trainer parses the log on-the-fly using _TrainLogParser object. It should be possible to access loss values using trainer.logparser.iterations[i]['loss'].
I would like to use a hyperparameter search algorithm to find the best hyperparameters (L1 and L2). For this I think the last loss value reported by the training algorithm can be useful.
Is there a way to get the last loss value computed during training?