#GlaDOS (Portal 1 & 2, Valve, Ov2 super trained) 150 Epochs
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im happy that i beat portal 1
both Portal games are so good man
Do yourself a favour and play both.
i have both anyways and im at the part in portal 2 where wheatley is in control.
"I am a potato"
Clap* Clap* Thank God Thats Still Working.
GLaDOS sounds like she's trapped me in a room and is trying to give me a lesson on lesbians
This is what it feels like to be a personality core or a turret in Aperture
this ones the best one
a simple robo effect thingy would make it way better fr
she has it if you speak like her in a monotone voice like the "s" and sometimes "f" have a robotic sound to them
ye but not every one is going to speak like that
or well ig if you OVERTRAIN it
to like FORCE it to be like the dataset
true, I do it when using the model with real time just to make it actually sound like her
I could never
I guess depending on what your model is supposed to sound like
even if you want it to sound human
from my tom foolery
sometimes the over trained models sounds better tbh
But well it might as well NOT be over trainned cause im just basing this on the two graphs of total loss
even tho thats NOT how you tell if its over training or not
grad norm and then loss fm and loss mel and so many other stuff
so i just never bother with graphs and tell by just testing and picking the best one
That's the best way to check anyway
A wha
Weights and Biases
its the holy of graphs
its a mess to set it up but its great
literally try looking at a guide for this shit
also ye its useless to set this up for RVC
RVC is NOT deserving of this
and not worth it
I honestly don't know too much about RVC or training ai models in general
same
you just do this and goofy parameters and go brrt
batch 4 for dataset of 10 min
and 8 for 20 min
we dont talk about the code level tweaks but
https://github.com/Enrop/RVC-Edits
Fr I always use batch 8 for everything because idk how it works
high batch size is learning fast and a low batch size is learning slower
so better for smaller datasets 
dont do batch size 1 
I had batch size 8 on a 9 second dataset of a lego tusken raider 
I probably should redo it with size 4 or something
not only slow
but it will make your model shit tier
i'd do 3 tbh
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