There are detailed changes below the next paragraph, you might need to expand this version changes box!

I'm uploading this "WIP version" of v6 as I'm not sure when / if I'll have the time / motivation to properly finish it up. It is roughly equivalent to v5 with the changes to the training process from v7 of my Dawn LoRA. It already fixes quite a few issues with v5 and should usually perform better. But it is not at the same level of improvement yet. If I'm not doing a "proper" v6 with major dataset changes, I might simply rename this version in the future.

Most of the changes (look at LoRA metadata for more details):

Updated to much newer Kohya scripts version (>3 months newer)
Updated training images
- Switched to keep original-ish aspect ratios (slightly cropped and resized to compatible SD 1.5 resolutions) where it makes sense instead of forcing squares
- Added regularization images to actually make trigger tag work correctly
  - 1 regularization image per training image
  - Generated by the base model at the same resolution, with the same tags (minus the activation tag)
  - Currently at half loss during training as they had a bit too much influence otherwise
  - With this, the LoRA now reverts back much closer to base model knowledge without the activation tag (which is correct!)
  - Might care a bit more about the positioning of the activation tag now as it was trained with "keep tokens" to keep the activation token at the front when shuffling
Normalized repeats to 1 (only using different values if ever in need of balancing datasets) and learning rates back to defaults
- Compensated with different epoch settings
Reverted back to training at 128 dims and a resize down to 32
- Results were better across the board and the resizing also removes a bit of noise as a bonus
- Used NO dynamic resize method as results for sv_fro@0.99 and sv_ratio@20 did not seem too different from or better than a simple resizing
Added training warmup of 10%
- Not sure if this had much impact, might remove again in the future
Added "scale weight norms" with value 1 during training
- Supposedly helps against overfitting and might make LoRAs more compatible with others
Used FreeU extension for example image generation to further improve results

Recommended weight: 1

Training model: Anything V3

Example image generation model: AbyssOrangeMix2 - Hardcore

[SD 1.5] Pokemon - Lillie / Lilie