Hi all, I am experimenting with some callbacks at the moment and I was wondering if there was a way to save the best models results into a pandas dataframe declared out of the function that I pass in? I am currently using the save_model callback to get the best value, but I want that value stored into a dataframe for comparison. Thank you!
I have a similar problem which I couldn’t find a solution for.
I train a NN with train_one_cycle() and now I need to store the written accuracy in a variable. Any ideas how this might work?
Here’s a blogpost that I found this on:
In the notebook on Hyperparameter Optimization they succeed in doing this by doing
float(learn.validate(learn.data.valid_dl)), which I succeeded in finding as well. This extracts the most recent accuracy as a float variable we can then load into pandas or what have you. Hopefully this may help some of you.