I have trained almost 80thousand examples within 2000 labels，valid acc almost 92%，but test result all example prob is blew 0.01.
I have tried tranning examples to predict.

Describe the bug
When using the LMFineTuner and specifying the learning_rate_finder_configs , an error is thrown when passing these configs to finetuner.find_learning_rate() as suggested in the documentation and in the [Colab example](https://colab.research.google.com/github/Novetta/adaptnlp/blob/master/tutor

It might be nice to, as a final step, show an instance of an actual inference on the model so a reader can "tie it all together". It isn't strictly useful, but for anyone who doesn't know a lot of the terminology it would bring it home.

"It turn out that Tucker decomposition yields lower accuracy loss than CP decomposition in my experiments, so the results below are all from Tucker decomposition."

what means "Tucker decomposition yields lower accuracy loss than CP decomposition" ?

and can the project be used in other cnn models?