| # Uzawa Reisa (Blue Archive) | |
| 宇沢レイサ (ブルーアーカイブ) / 우자와 레이사 (블루 아카이브) | |
| [**Download here.**](https://huggingface.co/khanon/lora-training/blob/main/reisa/chara-reisa-v3.safetensors) | |
| ## Table of Contents | |
| - [Preview](#preview) | |
| - [Usage](#usage) | |
| - [Training](#training) | |
| - [Revisions](#revisions) | |
| ## Preview | |
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| Unfortunately the model frequently struggles with Reisa's halo. | |
| ## Usage | |
| Use any or all of these tags to summon Reisa: `reisa, halo, low twintails, pink hair, purple eyes, star hair ornament` | |
| - Hair and eye tags are optional. | |
| She likes to make her `:d` expression by default. I included images tagged with other expressions, so you should be able to change it, but if not try adding `:d` to the negative prompt. | |
| For her normal outfit: `school uniform, grey shirt, blue jacket, pleated skirt, striped socks, backpack, sneakers` | |
| ## Training | |
| *Exact parameters are provided in the accompanying JSON files.* | |
| - Trained on a set of 89 images | |
| - 13 repeats | |
| - 3 batch size, 4 epochs | |
| - `(89*13) / 3 * 4` = 1543 steps | |
| - 0.0743 loss | |
| - 768x768 training resolution | |
| - `constant_with_warmup` scheduler instead of `cosine` | |
| - Initially tagged with WD1.4 Convnextv2 model. Tags were edited for accuracy and improved outfit consistency. Tags for facial expressions, camera angle, and image composition were added. | |
| - Used network_dimension 128 (same as usual) / network alpha 128 (default) | |
| - Trained without VAE. | |
| - [Training dataset available here.](https://mega.nz/folder/jyJAhJ5R#ebcamjoSq1quEZWlUh1qAQ) | |
| ## Revisions | |
| - v3 (2023-02-06) | |
| - Completely re-trained to correct issue where caption files were not being loaded correctly. New version should have more flexibility but requires additional outfit prompting. | |
| - v2b (2023-01-28) | |
| - Initial release. | |
| - **Issue:** caption files were completely ignored during training. As a result, prompting "reisa" grants a very strong effect, but the LoRA is highly overfit. | |
| - [Download available on Mega.co.nz repository.](https://mega.nz/folder/yjwGiIBD#w79CxW2-Cj66QmObg0zOdg) | |