description: <p>A LoRA for Adriana Chechik.</p><p></p><p><u>Process</u></p><ul><li><p>Images (71)</p><ul><li><p>Focus</p><ul><li><p>30 "full" body (waist/knees up)</p></li><li><p>17 upper body (chest and head)</p></li><li><p>18 close up (head and shoulders)</p></li><li><p>6 weird angles/poses (range from "full" body to upper body)</p></li></ul></li><li><p>Aspect ratio</p><ul><li><p>30 1:1</p></li><li><p>41 3:4</p></li></ul></li><li><p>Content (varied...)</p><ul><li><p>faces (1 eyes closed, half smiling, 1 eyeglasses)</p></li><li><p>lighting</p></li><li><p>clothing</p></li><li><p>makeup</p></li><li><p>background</p></li><li><p>pose</p></li></ul></li><li><p>Misc</p><ul><li><p>I try to exclude any images that have a busy/complex scene/background. Abnormal clothing, hand gestures, etc. are cropped out when possible. <strong>My rule of thumb is that if I wouldn't want the image to be generated by the LoRA, I don't include it in the dataset.</strong> There are some exceptions to this rule, but it is a good starting point to trim the dataset.</p></li><li><p>As many duplicate clothing items, facial expressions, poses, pieces of jewelry, etc. are excluded as possible, but it can often be hard to avoid this.</p></li><li><p>Images are cropped by hand and left at whatever # of pixels achieves the desired final image. They are kept to 3:4, 4:3, or 1:1 aspect ratios.</p></li><li><p>Many others have commented that 71 images is unnecessary, and that 20 or so will do. I prefer to be in the 40-80 range.</p></li></ul></li></ul></li><li><p>Captions</p><ul><li><p>All begin with "adriana chechik, a photo of a woman..."</p></li><li><p>I describe the clothing, jewelry, lighting, pose, angle, background, facial expression, makeup, and any other information I do not want showing up in the LoRA gens (abnormal hair color, for example) in sentence form.</p></li><li><p>I do not describe things I do want to show up in the LoRA, like eye color, hair color, skin tone, body proportions, etc.</p></li><li><p>I have experimented with adding a fake word "ohwx" to the captions with varying results. I did not do so for this LoRA.</p></li></ul></li><li><p>Training Params</p><ul><li><p>model: DreamshaperXL</p></li><li><p>text_encoder_lr: 0.0004</p></li><li><p>unet_lr: 0.0004</p></li><li><p>learning_rate: 0.0004</p></li><li><p>network_dim: 256</p></li><li><p>network_alpha: 1</p></li><li><p>lr_scheduler: constant</p></li><li><p>optimizer_type: Adafactor</p></li><li><p>train_batch_size: 1</p></li><li><p>dataset repeats: 20</p></li><li><p>epochs: 10 (sometimes up to 12 if I have a highly varied dataset)</p></li><li><p>max_train_steps: 20 * 10 * # of images (so for this one, it was 20 * 10 * 71 = 14,200)</p></li></ul></li><li><p>How is it so small?</p><ul><li><p>After training is complete, I am left with a 1.7gb safetensors file. I use the kohya gui to resize the lora with a rank of 256. This spits out a ~18mb safetensors file that is nearly identical to the 1.7gb file in practice.</p></li></ul></li></ul><p></p><p>I'm sure I missed something here, so let me know if there's any other info that would be useful.</p><p></p>
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name: Adriana Chechik SDXL
tags: woman celebrity pornstar adriana chechik