Normal for prediction on unannotated data to take a long time?
skylerilenstine opened this issue · 1 comments
skylerilenstine commented
When I run
python -m sesame.targetid --mode predict \
--model_name fn1.7-pretrained-targetid \
--raw_input myinput.txt
it just keeps running (the longest I let it run was about 3.5 hours before stopping it). The output looks like
[lr=0.01 clips=94 updates=100] epoch = 2.700 loss = 6.098552 train f1 = 0.7560
[lr=0.01 clips=94 updates=100] epoch = 2.800 loss = 6.038111 train f1 = 0.7584
[lr=0.01 clips=93 updates=100] epoch = 2.900 loss = 6.046757 train f1 = 0.7628
[dev epoch=2] loss = 3.448724 p = 0.7872 (1779.0/2260.0) r = 0.7513 (1779.0/2368.0) f1 = 0.7688 -- saving to logs/predict/best-targetid-1.7-model
[lr=0.01 clips=96 updates=100] epoch = 2.1000 loss = 6.093396 train f1 = 0.7125
[lr=0.01 clips=94 updates=100] epoch = 2.1100 loss = 6.180117 train f1 = 0.7512
[lr=0.01 clips=93 updates=100] epoch = 2.1200 loss = 6.178361 train f1 = 0.7239
[dev epoch=2] loss = 3.113013 p = 0.7686 (1857.0/2416.0) r = 0.7842 (1857.0/2368.0) f1 = 0.7763 -- saving to logs/predict/best-targetid-1.7-model
and keeps spilling over.
Is this normal for the first time? I'm using the pretrained models, so I don't know why it's running forever like this (I assume that training the models is what takes forever)
swabhs commented
This looks like you accidentally started training the model instead of predicting using a pretrained model?