I gathered 26 Colored HD images of Marylin Monroe. 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.
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 4 vectors per token. I switched to SD 1.5 EMA Only model for training.
I could have upscaled the images before extracting the faces so I could reduce blur.
Deleted byteorder and .data/serialization_id which wasn't able to pass the safety check
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