<h2 id="heading-13">Pre Training</h2><p>I gathered 34 images of Paris Hilton. I am only using Birme to crop the HD photos instead of using Faceswap to align the faces. Some of the images were full body as I wanted to retain her face even when zoomed out. I also flipped the images horizontally to increase the number of images to train on. This should increase variety. These are 512x512 images instead of 1024x1024 images because I don’t have the specs to train a 1024x1024 model. I used Blip captioning to generate the filewords and edited each individually to reduce potential hallucinations.</p><h2 id="heading-14">Training</h2><p>I used 0.005:100,0.0025:250,0.001:500,0.0005 for my learning rate. I am going for 10K training steps total. I am using a batch size of 1 with Gradient Accumulation Steps set to 3. I am running locally on a RTX 4090. I am using 12.5 out of 24 GB. The estimated time of completion is 2 hours. For the embedding I am using 8 vectors per token. I switched to SD 1.5 EMA Only model for training.</p><h2 id="heading-15">Things that I could have done better</h2><p>I could have upscaled the images before extracting the faces so I could reduce blur.</p>

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