How to train a tensorflow model that the output covers a huge range
You'll likely get better results if you preprocess to ensure that the output is mostly within [0, 1]. Since your output is "logarithmic", it may also help to make the output more linear; that is, take the log of your original outputs and rescale such that the logs are in [0, 1].
I've a dataset, where the output is logarithmic, I mean, it varies from values of 0.02 order to 15000 order, I should just train the model normally, or I should preprocess the output someway?
Thanks