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Training Notes (9B)

Summary

  • Base model: FLUX.2-klein-base-9B
  • LoRA rank: 16
  • Optimizer: AdamW8bit
  • Learning rate: 3e-5
  • Training steps (tentative best): 600

Dataset

  • Source images were collected from open-license panorama/HDRI archives on the web.
  • License policy was centered on permissive sources (CC0 / Public Domain), with part of the set including CC BY assets.
  • After preprocessing and filtering, training was run on a curated ERP pair set of about 1000 samples.

Preprocess / Pair Generation

  • Target format: ERP (equirectangular) 2:1
  • Source panoramas were normalized to ERP and cleaned (invalid aspect/failed reads removed).
  • Control images were generated by:
    • building a green ERP canvas,
    • sampling 1-3 reference patches,
    • projecting patches with a pinhole-based spherical mapping,
    • handling seam continuity with wrap-aware placement.
  • The model is trained to fill green regions while preserving visible reference context.