A weird question below.

Suppose you did a 10 fold cross-validation to show that a model is an unbiased estimator. And the results of the cross-validation also shows that training the model longer will improve its prediction accuracy. However you do not have the computational capacity to keep training all 10 folds. Is it scientifically correct to refit the model with all the data and continue training to obtain the final model. Will the results from the 10-fold cv be invalid? Would you still be able to conclude that the model is unbiased?

cheers