Open sharonapa opened 5 years ago
The current pretrained model (used to make the predictions in the README) took about 24-48 hours to train on a GTX1080Ti. You'd be looking at 72 hours-ish for a GTX1080.
If you feel adventurous, I am pretty sure that there are a lot of low-hanging fruits in the training code that could speed up the whole thing. Current data loading is not optimal for example.
Thanks, I've noticed it's taking some time to process one batch. I've few more questions : 1) where can I see your 200k data set? What was the parameters you ran the training? 2) the loss value I saw started from 6900 and dropping. Is this normal value? 3) my parameters were: 100k data set, batch size 32, 100k iterations (too much?) 4) can I speed up the lstm cells(or other ways to speed up) ? I've read that cudnnlstm does support variants sequence length. Thanks again.
בתאריך יום א׳, 31 במרץ 2019, 16:05, מאת Edouard Belval < notifications@github.com>:
The current pretrained model (used to make the predictions in the README) took about 24-48 hours to train on a GTX1080Ti. You'd be looking at 72 hours-ish for a GTX1080.
If you feel adventurous, I am pretty sure that there are a lot of low-hanging fruits in the training code that could speed up the whole thing. Current data loading is not optimal for example.
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Hi, can you approximate train time of 100k examples on Gtx 1080? I started it, seems very slow. Thanks.