Is 33% of test misclassification error rate considered good (or is it considered bad)?

I did a series of penalized continuation ratio regression on this data set that involves ordinal categorical response, and I am getting around 33-40% misclassification error rate on the test data set (the selection criteria I used was AIC and BIC; I also tried both forward and backward formulation).
Is this test misclassification rate considered bad (like should I keep try improving the model or would this be as good as it gets?)

Sounds like a silly question, but I am a student who is learning Stats so thank you for your understanding



Omega Contributor
Also what should come into play are the confidence intervals on this metric or do 33-40% represent those. Evaluation of metrics is always context specific. We have no idea if that is a high misclassification rate or not.