Hi all, I am new to deep learning. Kindly help me on this.
I have trained and saved a model
learn.save('trn_val=0.2_tst_res50-1')
and now, I need to create a new learner with the weights from the saved model. The new learner is something like the following
learn = cnn_learner(data_1, models.resnet50, metrics = accuracy)
Thanks for your help.
learn.load should work just fine on the new learner, passing in the old saved model:
learn.load('trn_val=0.2_tst_res50-1')Hi @nbharatula ,
I should first load using learn.load( 'trn_val=0.2_tst_res50-1') and then training a new model like
learn_new = cnn_learner(data_1, models.resnet50, metrics = accuracy) so that my new learner learn_new will start learning with the weights developed by the learner ‘learn’ right?
Create the new learner first then load the weights to the new learner. Does this new learner have a significant difference from the old? Same architecture? Same number of classes?
Hi @muellerzr, no significant difference. It is with the same architecture and classes.
Thans
Then yes. You’d generate a new learner and then do a learn.load() for your old weights
Thanks.
Just for clarification,
Should I first generate a new learner like
learn_new = cnn_learner(data_1, models.resnet50, metrics = accuracy)
then
learn.load('learn_old')
and then training further with
learn_new.fit(data_1, models.resnet50, metrics = accuracy) ?
Thanks a lot for helping me continuously. 
Not quite. Close! Learn_new.load since it’s your new learn object 
Then learn.fit(x) where x is our epochs. Learn_new.load takes care of the date etc
Yes, sorry. That (learn.fit) was a mistake in typing. So,
learn_new = cnn_learner(data_1, models.resnet50, metrics = accuracy)
learn_new.load('learn_old')
learn_new.fit(x)
am I right now?
Yep! Perfect!
@muellerzr thanks a lot. You have helped me in understanding another bit of deep learning with fastai.
Yes! Sorry I had to step away for a bit.
It’s OK @nbharatula .
Thanks for helping.