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Training with my own finetuned sdxl #25

@vikas784

Description

@vikas784

🚨 Issue: LoRA Not Updating Custom Fine-Tuned SDXL Model in SPO Training

I am training a model in two stages:

1️⃣ Stage 1 (Step-Aware Preference Model Training)

  • Trained on LAION dataset, outputs sdxl_step-aware_preference_model.bin.

2️⃣ Stage 2 (SPO Training)

  • Uses:
    • Base Model = Fine-tuned SDXL.
    • Reference Model = sdxl_step-aware_preference_model.bin.
  • Outputs LoRA adapters.

Issue 1: Model Weights Size Mismatch

  • My first-stage trained model (final_ckpts.bin) has two 5GB FP32 weight shards (total 10GB).
  • The Hugging Face repo (sdxl_step-aware_preference_model.bin) is only 5GB in FP16.
  • How is the Hugging Face model so much smaller?

Issue 2: LoRA Not Updating Fine-Tuned Model

  • When I apply LoRA to my fine-tuned SDXL, it says "no modules changed".
  • But when I apply it to Hugging Face’s SDXL, it works.
  • Why does it not work on my fine-tuned model?

Issue 3: UNet Source in Hugging Face Repo

  • The Hugging Face repo contains a unet file, but I cannot find where it came from.
  • Could you clarify how it was generated?

Reproducibility Steps

  1. Train Stage 1 model → Get final_ckpts.bin (10GB).
  2. Convert to FP16 → Expected size should be 5GB, but mismatch with Hugging Face repo.
  3. Train Stage 2 using sdxl_step-aware_preference_model.bin.
  4. Apply LoRA to my fine-tuned SDXL → No changes.
  5. Apply LoRA to Hugging Face SDXL → Works fine.

Expected Behavior

  • LoRA should update the fine-tuned SDXL model correctly.
  • Model size should match expectations.
  • Source of the UNet in Hugging Face repo should be clear.

Additional Context

Any insights on these issues would be helpful. Thanks!

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