Hi li0218,
This means that your model may have generalized well. You could try increasing the network size to try to get a better fit.
Precaution : Have a look at the confusion matrix of your model for the training and test data. And compare them with the ratio of positive and negative classes in your data. It may be happening that your model is mostly predicting one class, and the accuracy simply reflects the proportion of that class in your data.
Hope this helps!
Regards