Why My Architectural LoRA Kept Inventing Extra Windows

A focused diagnosis of repetitive facade priors and ambiguous captions. The reliable path is to make inputs, assumptions, and acceptance checks visible before producing a new adapter or deployment artifact. This note uses an illustrative workflow rather than a claim about a particular organization or production outcome.

Establish the boundary

Describe the visible failure across elevations and sections. Start with a versioned source set and preserve stable identifiers through every transformation. That makes it possible to compare a later output with the exact examples, configuration, and review rule that produced the earlier one. Record deterministic failures separately from reviewer judgment so that a retry does not silently alter the work.

Audit window frequency, facade regularity, and caption vocabulary

Audit window frequency, facade regularity, and caption vocabulary. Start with a versioned source set and preserve stable identifiers through every transformation. That makes it possible to compare a later output with the exact examples, configuration, and review rule that produced the earlier one. Record deterministic failures separately from reviewer judgment so that a retry does not silently alter the work.

Base-model prior from adapter amplification using non-trigger prompts

Separate base-model prior from adapter amplification using non-trigger prompts. Start with a versioned source set and preserve stable identifiers through every transformation. That makes it possible to compare a later output with the exact examples, configuration, and review rule that produced the earlier one. Record deterministic failures separately from reviewer judgment so that a retry does not silently alter the work.

Rebalance examples and add explicit solid-wall cases

Rebalance examples and add explicit solid-wall cases. Start with a versioned source set and preserve stable identifiers through every transformation. That makes it possible to compare a later output with the exact examples, configuration, and review rule that produced the earlier one. Record deterministic failures separately from reviewer judgment so that a retry does not silently alter the work.

Revised checkpoints with fixed seeds

Compare revised checkpoints with fixed seeds. Start with a versioned source set and preserve stable identifiers through every transformation. That makes it possible to compare a later output with the exact examples, configuration, and review rule that produced the earlier one. Record deterministic failures separately from reviewer judgment so that a retry does not silently alter the work.

Remaining limits and when geometric conditioning is required

Explain remaining limits and when geometric conditioning is required. Start with a versioned source set and preserve stable identifiers through every transformation. That makes it possible to compare a later output with the exact examples, configuration, and review rule that produced the earlier one. Record deterministic failures separately from reviewer judgment so that a retry does not silently alter the work.

Practical check

Dataset audit script counting caption tokens. The following minimal command or script is intended as a preflight check. It is deliberately small: its job is to expose missing structure before a longer run or a release review.

dock finetune \\
  --base stabilityai/stable-diffusion-xl-base-1.0 \\
  --data ./dataset.jsonl \\
  --rank 16 \\
  --alpha 32 \\
  --epochs 3 \\
  --seed 42

Release decision

A useful release record names the input version, the transformation or runtime configuration, the validation slice, and the remaining limitation. Claiming LoRA can guarantee code-compliant architecture. When evidence is incomplete, keep the artifact private, add the missing check, and preserve the failing example as a future regression case.

Keep the workflow idempotent. Repeating the same preparation step on the same input should not append metadata, discard additional detail, or change stable identifiers. Idempotence makes retries safe and turns unexpected differences into visible defects.

Review results by failure category instead of relying on a single blended score. A small number of high-risk failures can matter more than an improvement on common cases, especially when the adapter feeds a downstream queue or release process.

The final comparison should keep decoding, prompt formatting, and file versions fixed. If several variables move together, the result may look better while leaving the actual cause of the improvement unknown.

Retain both accepted and rejected examples. A concise rejected case with an expected outcome is a durable test asset and prevents the next contributor from rediscovering the same edge condition.