Notes: I will no longer be flipping the images horizontally as this “muddies the mirror”. Also I am training on modified PT that has had byteorder and .data/serialization_id removed. This allows it to pass the safety checker!

Pre Training

I gathered 19 images of Pamela Anderson. 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 used Blip captioning to generate the filewords and edited each individually to reduce potential hallucinations.

Training

I used 0.005:100,0.0025:250,0.001:500,0.0005 for my learning rate. I am going for 5K 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.

Things that I could have done better

I could have upscaled the images before extracting the faces so I could reduce blur.