I am running k-fold cross validation on my training data, and then choosing the best set of hyper parameters, re-training on the training data and testing on a new (unseen) testing data. I am getting the following testing results (results on the unseen data):
R^2: 1.000 Adj R^2: 1.000 RMSE: 0.081 MSE: 0.007 MAE: 0.045 MAPE: 0.058
Can $R^2$ have a value of 1.00 but RMSE have a value of 0.081? Doesn't an $R^2$ of value 1 indicate no errors at all?