| This is my first time doing any sort of Stable Diffusion training so I went through a lot of trial and error. Here are my findings in case it helps anyone. | |
| # Training | |
| *All parameters are provided in the accompanying JSON files.* | |
| - Trained on 138 curated images, repeated 8 times (1104 total images / 3 batchsize = 368 iterations) | |
| - I pruned most images with white backgrounds because I felt they might have been negatively impacting my results early on, but in hindsight I think that was bad training parameters instead. | |
| - Dataset was tagged with WD1.4 interrogator. Shuffling was disabled. | |
| - `mutsuki, blue archive` were added to the start of each caption. | |
| - Two variants included; one trained at 512px max resolution, and another trained at 768px max resolution. All other params identical. | |
| - Trained on RTX 4090 for about 2min30sec (512px variant) and 6min30sec (768px variant) | |
| - I tried using higher batch sizes with the 512px variant for faster training, but the results seemed noticably worse. | |
| - Small batch sizes seem to work better even when you have the VRAM for 10 or 12, so I instead put the VRAM towards training a higher resolution variant. | |
| # Usage | |
| Mutsuki needs a few tags to be summoned reliably. Some common tags in her dataset: | |
| `1girl, halo, side ponytail, long hair, white hair, purple eyes, jacket, red skirt, light grin, small breasts` | |
| You can add or ignore `mutsuki, blue archive`; while they were in her captions, they don't seem to be particularly strong for some reason. | |
| You can use the 512px or 768px variants. I want to say the 768px one is better, but it's hard to say definitively. Give both a shot and post your findings. | |
| Weight 0.80-1.05 should work well depending on model. | |