When I run my three different neural networks I obtain the following learning curves using MSE.
I believe that my model base is okay and is not overfitting or underfitting. Furthermore, I believe that my model small is underfitting due to high training error and high validation error. However, I'm not sure about model big. Taking the square root of the MSE the RMSE of both the train set and validation set in model big is lower than model base. Yet on the picture and from what I have learned in class it is still underfitting?
Is this correct? I just do not understand how the model performs well but it does not learn looking at the picture.
Thank you in advance.