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# Igusa Haruka (Blue Archive)
伊草ハルカ (ブルーアーカイブ) / 이구사 하루카 (블루 아카이브) / 伊草春香 (碧蓝档案)

[**Download here.**](https://huggingface.co/khanon/lora-training/blob/main/haruka/chara-haruka-v1c.safetensors)

## Table of Contents
- [Preview](#preview)
- [Usage](#usage)
- [Training](#training)
- [Revisions](#revisions)

## Preview
![Haruka portrait](chara-haruka-v1c.png)
![Haruka preview 1](example-001b-v1c.png)
![Haruka preview 2](example-002b-v1c.png)
![Haruka preview 3](example-003b-v1c.png)

## Usage
Use any or all of the following tags to summon Haruka: `haruka, 1girl, halo, short hair with long locks, purple eyes`

For her normal outfit: `school uniform, hairclip, purple jacket, collared shirt, juliet sleeves, belt, miniskirt, black skirt, boots`
- The AI is slightly stubborn with Haruka's normal outfit, likely because she doesn't have much art that does not feature long sleeves of some sort.
- To remove her jacket sleeves, prompt `sleeveless` and use `long sleeves` in the negative prompt.
- To remove the purple bowtie/tie clip, prompt `collarbone` and use `bowtie` in the negative prompt.

For her nervous/creepy smile: `nervous smile, nervous, sweat, wavy mouth, [closed mouth:parted lips:0.75]`
- Use `sanpaku, constricted pupils, crazy eyes, yandere` or similar for more intense expressions.

[Here is a list of all tags including in the training dataset, sorted by frequency.](all_tags.txt)

## Training
*Exact parameters are provided in the accompanying JSON files.*
- Trained on a set of 143 images.
  - 138 without "multiple views" (9 repeats)
  - 5 "multiple views" (4 repeats)
  - 3 batch size, 4 epochs
  - `(138 * 9 + 5 * 4) / 3 * 4` = 1683 steps
- 0.083 loss
- Initially tagged with WD1.4 swin-v2 model. Tags pruned/edited for consistency.
  - [Tagging methodology detailed here.](tagging%20methodology.md)
- `constant_with_warmup` scheduler
- 1.5e-5 text encoder LR
- 1.5e-4 unet LR
- 1e-5 optimizer LR
- Used network_dimension 128 (same as usual) / network alpha 128 (default)
  - Resized to 32 after training
- Training resolution 832x832.
- Trained without VAE.

## Revisions
- v1b (2023-02-23)
  - Initial release.