The Mean of squared residuals: 0.05206834 in your output is the out-of-bag MSE estimate. Just take the square root:

sqrt (tail (Rf_model$mse, 1))

(Apparently, $mse stores the oob MSE observed for bagging 1 : n trees, the last one is the one we need.)

You can double check by manually calculating RMSE from the oob predictions:

sqrt (mean ((Rf_model$predicted - whole_data$target^2)) 

The Mean of squared residuals: 0.05206834 in your output is the out-of-bag MSE estimate. Just take the square root:

sqrt (tail (Rf_model$mse, 1))

(Apparently, $mse stores the oob MSE observed for bagging 1 : n trees, the last one is the one we need.)

You can double check by manually calculating RMSE from the oob predictions:

sqrt (mean ((Rf_model$predicted - whole_data$target)^2)