Closed prontiol closed 7 years ago
I've been playing with this repo for half a day and had good luck training datasets from 500KiB (Donald Trump Tweets) to 11MiB (KJV Bible). With default settings the train_loss
drops to around 1.2 quite quickly (10 minutes w/ 1x GPU). Going below that takes longer time with mixed subjective performance gains.
I haven't calculated the theoretical minimum, perhaps 1? Need to read up more and check into the stuff about perplexity
as well.
But directly to your question, how does the sample output look after training for an hour or so? Is it beginning to work at least, or just noise?
A few thoughts:
num_layers
1 or 2 to start.rnn_size
, num_layers
, seq_length
take longer to convergence on low train_loss
values in my limited experience.Good luck! Hope you've had success!
I hope you've had better luck, we also just added a number of PRs this weekend. Keep an eye out for a better README w/ descriptions of the parameters.
If you do have some luck feel free to post back here with your settings, data sets, and results!
Thanks
I am trying to build my network with 21M text file, but whatever I do, it gets stuck at train_loss ~1.6 and does not progress any more. I tried changing:
But nothing helps and I always get my network to stop learning and stuck at about 1.6-1.7 train_loss. How can I diagnose the problem? Can someone advise?