| # Yuragi Momoka (Blue Archive) | |
| 由良木モモカ (ブルーアーカイブ) / 유라기 모모카 (블루 아카이브) / 由良木桃香 (碧蓝档案) | |
| [**Download here.**](https://huggingface.co/khanon/lora-training/blob/main/momoka/chara-momoka-v1c.safetensors) | |
| ## Table of Contents | |
| - [Preview](#preview) | |
| - [Usage](#usage) | |
| - [Training](#training) | |
| - [Revisions](#revisions) | |
| ## Preview | |
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| ## Usage | |
| Use any or all of the following tags to summon momoka: `momoka, halo, short twintails, horns, bright pupils, pointy ears, hair ornament, ahoge` | |
| - Add `(dragon tail:1.3)` for her tail (even though I'm not quite sure Momoka is truly a dragon?) | |
| For her normal outfit: `sleeveless dress, collared dress, blue necktie, white open jacket, off shoulder, loose socks, white shoes` | |
| - Add `frilled dress` if the frills at the bottom of her dress are not correctly displayed. | |
| For her accessories: `potato chips, bag of chips, holding food` | |
| For her smug expression: `smug, open mouth, sharp teeth, :3, :d` | |
| - Alternatively, `smug, grin, sharp teeth, smile` for a toothy grin | |
| [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 94 images. | |
| - 13 repeats | |
| - 3 batch size, 4 epochs | |
| - `(94 * 13) / 3 * 4` = 1654 steps | |
| - 0.0737 loss | |
| - Initially tagged with WD1.4 swin-v2 model. Tags pruned/edited for consistency. | |
| - `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 24 after training | |
| - This LoRA seemed very slightly overtrained, perhaps due to smaller dataset, so resizing to 24 appeared a bit better than 32. | |
| - Training resolution 832x832. | |
| - This one also came out better at 832 vs 768. | |
| - It's not clear to me why some LoRAs perform substantially better at 768 and others at 832. | |
| - Trained without VAE. | |
| ## Revisions | |
| - v1c (2023-02-19) | |
| - Initial release. | |