Hi All,
I’m trying to reuse some code from lesson3 (nlp on mnist) to build a language model.
bs=48
data_lm = (TextList.from_df(data)
.split_by_rand_pct(0.1)
#We randomly split and keep 10% (10,000 reviews) for validation
.label_for_lm()
#We want to do a language model so we label accordingly
.databunch(bs=bs))
learn = language_model_learner(data_lm, AWD_LSTM, drop_mult=0.3)
learn.lr_find()
However, I’m not getting a validation loss on the learning rate finder. I’m not sure why as I can get a validation loss when fitting the actual model.
Any tips?
Thanks
epoch | train_loss | valid_loss | accuracy | time |
---|---|---|---|---|
0 | 3.960693 | #na# | 00:33 | |
1 | 3.958584 | #na# | 00:36 | |
2 | 3.957576 | #na# | 00:35 | |
3 | 3.948066 | #na# | 00:38 | |
4 | 3.916027 | #na# | 00:36 | |
5 | 3.765308 | #na# | 00:35 | |
6 | 3.367810 | #na# | 00:37 | |
7 | 3.159484 | #na# | 00:37 | |
8 | 9.506555 | #na# | 01:27 |