SDXL Train Validation Settings

When you're validating an SDXL LoRA mid-training - generating preview images so you can watch the thing learn - you need to tell it how to render those previews. SDXLTrainValidationSettings is that control panel. It bundles the sampler, resolution, step count, and seed into one settings object that feeds the validation node.

Think of it as the "generation settings" for your training previews. It doesn't affect the training itself one bit - only what the sample images look like. But getting it right is what makes those previews actually useful for judging progress.

How it works

The node outputs validation_settings (type VALSETTINGS), which you wire into the validation_settings input of a validation node. The inputs are exactly what you'd set for a normal SDXL generation:

• steps (default 20) - sampling steps for the preview. 20 is plenty for a quick check; you don't need a slow high-step render just to see if likeness is emerging.
• width / height (default 1024×1024) - SDXL's native resolution. Keep it here unless you have a reason to preview at another aspect.
• guidance_scale (default 7.5) - CFG for the preview, the familiar SDXL value.
• sampler (default dpm_2) - the dropdown includes euler, euler_a, ddim, dpmsolver, heun, dpm_2, dpm_2_a and more. Any standard SDXL sampler is fine; pick one you'd actually generate with.
• seed (default 42) - and this is the important one. Keep the seed fixed across all your validations so the only thing changing between previews is the training, not the random draw.

Why the fixed seed matters

This is the whole trick to useful validation. If your seed wanders between checkpoints, you can't tell whether a better-looking preview means the LoRA improved or you just got a luckier roll. Lock the seed and the same prompt renders the same composition every time, so a change in the image is a change in the training. That's how you spot the checkpoint where likeness peaks before overfitting.

Installing the pack

ComfyUI Manager: search ComfyUI Flux Trainer, install, restart. Or:

cd ComfyUI/custom_nodes
git clone https://github.com/kijai/ComfyUI-FluxTrainer
pip install -r ComfyUI-FluxTrainer/requirements.txt

Torch 2.4.0+ recommended, plus kijai's ComfyUI-KJNodes for the example workflows.

Common issues

Previews are slow and stealing training time. Every validation is a full SDXL generation on top of training. High step counts or huge resolutions make each preview expensive. Keep steps around 20 and resolution at 1024 - this is a sanity check, not a final render.

This is SDXL-specific. The node's sampler list and 7.5 CFG default are tuned for SDXL. It pairs with the SDXL training path; a Flux validation flow uses its own settings and much lower guidance.

Changing settings won't fix a bad train. If previews look wrong, the fix is in the dataset, learning rate, or step count - not in the validation sampler. This node only changes how you look at the model, never what it learned.