We have trained a model on one large csv file and save the model
THen a month later we get a new csv file and want to continue training on it.
I have tried:
learner = load_learner('my_model.pth') my_new_df = pd.read_csv('new_file.csv") learner.dls.train = my_new_df learner.fit_one_cycle(1) returns an error string indices must be integers
I thought that dls object inside the learner is handling the preprocessing - e.g. normalizing etc.