<h2 id="heading-9">Pre Training</h2><p>I gathered 34 images of Salma Hayek. Majority of photos were from red carpet events and less from movies. 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. I added a 1 to the end of Hayek on the embedding name to ensure there is no mixing with previously trained images of her.</p><h2 id="heading-10">Training</h2><p>I used 0.005:100:0,0.0025:250,0.001:500,0.0005:1000,0.00025 for my learning rate. I am going for 2.5K training steps total. I am using a batch size of 1 with Gradient Accumulation Steps set to 3. I am running on a RTX 4090 on the cloud. I am using 12.5 out of 24 GB. The estimated time of completion is .5 hours. For the embedding I am using 8 vectors per token. I switched to SD 1.5 EMA Only model for training.</p>

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