I've developed a model that predicts a future value of a parameter for the next 72 hours (only 11 hours presented on the chart). I've obtained the hyperparameters for my model with use of RandomizedSearchCV. Than I've retrained my model with those hyperparameters on the development (train) set and tested its performance on the test set (peace of data used only for this purpose). The chart below shows performance of the model on the train and test set. And here is my question: how can I say whether the model has high variance or bias? Is it safe to just assume that since the MAEs of the train and test sets are similar and not spectacularly huge then the RandomizedSearchCV just got me good hyperparameters ant its just fine?