[BUG]

[rossbalch]

Describe the bug
Training of LSTM models currently seems to currently have issues. Using the default parameters in the GUI to train the same re-amp as a model trained in the default Wavenet parameters yielded wildly different results. I also try the same in the CLI version with a different re-amp and while some seemed to train correctly, there was still some weird behavior.

To Reproduce
I have run replicates and gotten the same results multiple times. I used the standard NAM v3 input file, as well as some custom inputs (such as Aida-X input file, as they are using LSTM for their RT-Neural implementation). I tried an ny of both 8192 and 32768 as suggested in the config files. I further tried with larger LSTM models like 32 hidden units, and 2 layers. The increase in size did not help. In fact it made the ESR worse as seen in the picture above.

Desktop (please complete the following information):
Win 1124H2 - Anaconda Powershell
Both GUI and CLI NAM Trainer
v 0.10.0