All notes · Generative AI
I trained a LoRA on my own face. Here's every mistake.
Dataset curation, captioning, and rank/alpha sweeps on Flux — and why 18 photos beat 60.
What I was trying to do
I wanted a Flux LoRA that could put my face in a scene without turning every portrait into the same lighting setup.
What actually mattered
The first dataset was too big and too same-y. Cropped phone photos, repeated backgrounds, captions that just said my name. The model memorised the room.
Eighteen photos with distinct captions — clothes, camera, background — beat the sixty-photo pile. Rank and alpha needed a short sweep, not a weekend of random numbers.
What I would not repeat
Training on images I also used as the site hero, then being surprised when the hero looked like the training set. Hold a few frames out.
The portraits on this site are generated from that LoRA. The writeup is the part I can stand behind: curation beat volume.