How to choose a model for this cross-validation curve?
Choosing the best validation accuracy is the common practice, since validation is unseen data.

Sometimes you might have over-fitting to the validation set, mainly if it is too small or no very representative of the data (for example if it has considerably more examples of one class, thus a good model would be a model that says that (almost) everything belongs to that class).

If you are worried about over-fitting, you could increase your regularization strength.