Loading train data: 6%|█▊ | 25/395 [01:08<08:03, 1.31s/it]INFO:ljs_base:Train Epoch: 6 [6%]
INFO:ljs_base:[2.675187349319458, 1.905822992324829, 2.1355035305023193, 27.08325958251953, 1.6539193391799927, 1.324233889579773, 2000, 0.0001997751124671936]
DEBUG:matplotlib:matplotlib data path: /opt/conda/envs/vits/lib/python3.11/site-packages/matplotlib/mpl-data
DEBUG:matplotlib:CONFIGDIR=/home/ubuntu/.config/matplotlib
DEBUG:matplotlib:interactive is False
DEBUG:matplotlib:platform is linux
INFO:ljs_base:Saving model and optimizer state at iteration 6 to ./logs/ljs_base/G_2000.pth
INFO:ljs_base:Saving model and optimizer state at iteration 6 to ./logs/ljs_base/D_2000.pth
Loading train data: 26%|███████ | 103/395 [02:50<04:48, 1.01it/s]
I am trying to train with the LJ Speech Dataset in aws ec2 instance.
Using p3.2xlarge instance It is kind of very slow. Is there any kind of optimization I can do?
And while training how much time did it take for you?
I am trying to train with the LJ Speech Dataset in aws ec2 instance.
Using p3.2xlarge instance It is kind of very slow. Is there any kind of optimization I can do?
And while training how much time did it take for you?