Loading pre-trained text_classifier_learner with new data clas


In one of the lectures, Jeremy mentioned that we can improve the model performance by fixing the high loss data points and training the model with a lower learning rate. I am wondering how to do this.

    learn = text_classifier_learner(data_clas, AWD_LSTM, drop_mult=0.4, callback_fns=[csv_logger])
    learn.load_encoder(os.path.join(data_enc_path, data_enc_name))
    learn.fit_one_cycle(cycle, 1e-2, moms=(0.8,0.7))

I have exported the above using
learn.export(file = ‘labeled_only_model.pkl’)

I would like to load a new data clas with just corrected high loss file and the previously exported learn (labeled_only_model.pkl) and train the again. How do I correctly load the weights and the most recent vocab correctly?

Thank you!