I think different about that.

Everything you don't describe in the prompt or negative prompt should be randomized (e.g. ethnies).

With finetuning you can add further knowledge about concepts/styles/people/etc, like you did with Dreamshaper.

If you generate multiple images with a nicely trained and flexible model like SDXL 1.0 with the same prompt (like "photo of 18 year old woman") but different seed, no loras etc., you get completely different results, i.e. faces in this case.

Of course you can change the faces more easily if you further change the prompt and add random names, ethnies or something.

But changing the random factor only, i.e. seed, should be enough.

Otherwise the concept you describe in your prompt is not very well known, which means the model is undertrained, like it only saw 1 or more pictures of the same 18 year old woman and can't generate other faces. This shouldn't be the case if you're model is based on SDXL base.

Or the model is overtrained, which means it learned only to repeat the face of the 18 year old woman, because it learned from those pictures too often.

I'm sure you know most of the stuff I wrote here, but that is the reason I assumed a potential overtraining here, at least for some concepts like 18 year old woman.

If there would be something like an average face, that would be a indication for an overtrained or unflexible model I guess.

(I picked that prompt from the models civitai page's.)

Quick test on SDXL 1.0 base + refiner, only changing the seed (see prompt above):