# Confusion for considering accuracy or standard deviation in selecting the best parameters

I have a model with a various parameters to test.

The size of the dataset I have is not really large (~500 documents).

My issue is that when I test the parameters using 10 CV, some of them produce high accuracy value but the Standard deviation value of the folds (accuracy values of the folds) is high.

ex.

Model setup 1: acc: 0.81, STD: 0.23
Model setup 2: acc: 0.76, STD: 0.05


Setup 1 has higher accuracy but the std is high, where setup 2 has lower accuracy but with more stable results.

Thus, how can I pick the best model?