Update README.md

README.md

@@ -22,7 +22,6 @@ I`m trying to find a way to optimize the captioning of identifiers. I`ll write d
 ## Ningguang/凝光
 ### Brief intro
 LORA of Ningguang, with two costumes in game. civitAI page [Download](https://civitai.com/models/8546/ningguang)
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 ### Training dataset
 #### Default costume
 72 images in total, in folder "30_Ningguang"
@@ -36,29 +35,45 @@ LORA of Ningguang, with two costumes in game. civitAI page [Download](https://ci
 * 15 normal 360 3D model snapshots
 * 2 nude illustrations
 * 15 nude 360 3D model snapshots
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 ### Captioning
 WD14 captioning instead of the deepdanbooru caption was used, since the former one will not crop/resize the images. Threshold are usually set to 0.75-0.8. since I don't like to have a very long and sometimes inaccurate caption for my training data. After captionin is done, I added "ningguang \ \(genshin impact\ \)" after "1girl" to every caption file of the default costume, and "ningguang \ \(orchid's evening gown\ \) \ \(genshin impact\ \)" to the orchid costume. Some of the caption files were empty so I have to manually type the words. 
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 ### Training setup
 Trained with Kohya_SS stable diffusion trainer Base model was [Anything V3.0 full](https://huggingface.co/Linaqruf/anything-v3.0/blob/main/anything-v3-fp32-pruned.safetensors) Trainig process consist of two phases. The first one with default parameters of:
 * learning_rate: 0.0001
 * text_encoder_lr: 5e-5
 * unet_lr: 0.0001 and 6 epoch,
 After phase 1, choose the one with the best result (a little bit underfitting, no over fitting, and the two costume are seperated), which is the 6th one. Then trained with 1/10 of the original LR for another 7 epochs.
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 ### Result
 ![sample1](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/9573a553-c456-4c36-c029-f2955fe52800/width=480)
 ![sample2](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/c7709515-4537-4501-fe87-296734995700/width=480)
 ![sample3](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/38d47c4a-6ba5-4925-5a56-e8701856a100/width=480) 
 ![sample4](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/b60aa7f4-6f63-46fb-381f-05b11f4afe00/width=480)
 
+## Barbara/芭芭拉
+### Brief intro
+LORA of Barbara, with two costumes in game.
+### Training dataset
+#### Default costume
+164 images in total, in folder "10_barbara_(genshin_impact) 1girl"
+* 104 illustrations, bothSFW and NSFW, handpicked to ensure best quality
+* 30 normal 360 3D model snapshots
+* 30 nude 360 3D model snapshots
+#### Summertime swimsuit
+94 imges in total, in folder "16_barbara_(summertime_sparkle)_(genshin_impact) 1girl"
+* 64 illustrations, bothSFW and NSFW, handpicked to ensure best quality
+* 30 normal 360 3D model snapshots
+### Captioning
+It was the first time that the standard Danbooru style prompt was used for captioning. "barbara_(genshin_impact)" and "barbara_(summertime_sparkle)_(genshin_impact)" were added to each costume respectively.
+### Training setup
+Defalut LR fo 4 epochs, then 1/10 default LR for another 8 epochs.
+Trainig basing on anything v3.
+Total steps is: (4+8)x(164x10+94x16)=37,728
+### results
 
 # Charater from Honkai impact
 ## Elysia/爱莉希雅
 ### Brief intro
 LORA of Elysia, with 4 costumes in game. civitAI page [Download](https://civitai.com/models/14616)
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 ### Training dataset
 #### Default costume/Miss Pink Elf
 70 images in total, in folder "14_Elysia (miss pink elf) 1girl"
@@ -77,16 +92,13 @@ LORA of Elysia, with 4 costumes in game. civitAI page [Download](https://civitai
 * 14 normal illustrations, non-nude
 * 60 normal 360 3D model snapshots
 In addition, I have also included 12 images with non-official costumes in a new folder "10_Elysia 1girl"
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 ### Captioning
 WD14 captioning instead of the deepdanbooru caption was used, since the former one will not crop/resize the images. Threshold are usually set to 0.75-0.8. since I don't like to have a very long and sometimes inaccurate caption for my training data. After captionin is done, I added "elysia \ \(miss pink elf\ \) \ \(honkai impact\ \)", "elysia \ \(herrscher of human:ego\ \) \ \(honkai impact\ \)", "Elysia-maid", "Elysia-swimsuit" and "1girl, elysia \ \(honkai impact\ \)" to the captioning respectively as identifiers.
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 ### Training setup
 Trained with Kohya_SS stable diffusion trainer Base model was [Anything V3.0 full](https://huggingface.co/Linaqruf/anything-v3.0/blob/main/anything-v3-fp32-pruned.safetensors) Trainig process consist of two phases. The first one with default parameters of:
 * learning_rate: 0.0001
 * text_encoder_lr: 5e-5
 * unet_lr: 0.0001 and 4 epoch,
 After phase 1, choose the one with the best result (a little bit underfitting, no over fitting, and the two costume are seperated), which is the 6th one. Then trained with 1/10 of the original LR for another 8 epochs.
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 ### Result
 ![sample1](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/9a699f92-b026-4efb-9714-6d6e2675f400/width=800/174757)