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README.md
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license: openrail
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This is my attempt at creating a truely open source SDXL model that people might be interested in using....
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and perhaps copying the spirit and creating other open source models.
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Once I got down to <200 images images, and had a reasonable lora, I decided to give a full finetune a try, "the hard way"
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(ie: no adaptive optimizer)
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So, I played with the learning rate a little, and.. that was it?
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Nope!
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I was training with 100 epoch, and having onetrainer do an image sample every few epochs. But, due to disk space,
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I was only doing saves every 20 or so.
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When I looked back at the
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---
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license: openrail
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tags:
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- sdxl
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---
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This is my attempt at creating a truely open source SDXL model that people might be interested in using....
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and perhaps copying the spirit and creating other open source models.
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Once I got down to <200 images images, and had a reasonable lora, I decided to give a full finetune a try, "the hard way"
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(ie: no adaptive optimizer)
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So, I set EMA=CPU (because not enough VRAM to fit in GPU) played with the learning rate a little, and.. that was it?
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Nope!
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I was training with 100 epoch, and having onetrainer do an image sample every few epochs. But, due to disk space,
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I was only doing saves every 20 or so.
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When I looked back at the image samples, I noticed that the one I liked best, was actually around epoch 72..
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I didnt know what e71,72, or 73 looked like... and I didnt even have a save for 72 either!
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What I did have, was a save at 70. So I configured OneTrainer to do a new run, starting with my saved model at 70.
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This time, however, I disabled warmup, and also EMA.
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I then set OneTrainer to make a save every epoch, and a preview every epoch.
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The previews looked kind of like my original series!
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Thus encouraged, I decided to try out all 10 of the models, just in case.
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It turns out that I liked epoch 78/100 the best.. so here we are :)
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