Fine-tuning Architecture
Fine-tuning Architecture
Section titled “Fine-tuning Architecture”This guide shows an end-to-end workflow for improving finetuning_architecture health in production fine-tuning systems.
Workflow
Section titled “Workflow”- Run a fine-tuning architecture audit.
- Triage findings by risk family and blast radius.
- Apply targeted remediation.
- Enforce policy gates in CI.
- Prevent regressions with baseline checks.
1) Run an Audit
Section titled “1) Run an Audit”# Focused fine-tuning metricarxo analyze --path . --metric finetuning_architecture --format json# AI preset (includes finetuning_architecture)arxo analyze --path . --preset ai --format json2) Triage Findings
Section titled “2) Triage Findings”Prioritize in this order:
method_integrity_score,checkpoint_eval_lineage_score,artifact_trust_surface_scorebase_model_versioning_score,run_lineage_score,determinism_envelope_scoreeval_absence_score,dataset_contamination_score,distillation_integrity_scoreprivacy_recordkeeping_score,model_artifact_access_score,adapter_isolation_scoreoom_risk_score,cost_tracking_score,artifact_metadata_score,prompt_format_inconsistency_score
Then inspect composite movement:
finetuning_architecture.overall_finetuning_healthfinetuning_architecture.reproducibility_scorefinetuning_architecture.data_integrity_scorefinetuning_architecture.safety_governance_score
3) Apply Fixes by Track
Section titled “3) Apply Fixes by Track”- Method track: enforce profile-specific invariants (
dpo,ppo,rft,grpo,rloo,distill). - Repro track: base/tokenizer pinning, run passport, determinism envelope, checkpoint-eval linkage.
- Data/eval track: explicit split strategy, contamination checks, eval maturity, distillation provenance/parity.
- Safety/governance track: trust surface hardening, access controls, privacy budget logging, technical recordkeeping.
- Ops/cost track: OOM controls, budget and throughput tracking.
Use the Remediation Playbook for detector-by-detector fixes.
4) Enforce in CI
Section titled “4) Enforce in CI”Use profiles from Policy and CI Gates.
arxo analyze --path . --preset ai --config arxo.yml --fail-fastRecommended rollout:
- Start with warning-level thresholds.
- Fix recurring low-score categories in central modules.
- Promote critical gates to
errorafter score trend stabilizes.
5) Baseline and Monorepo Rollout
Section titled “5) Baseline and Monorepo Rollout”- Enable baseline no-regression checks against
origin/main. - Start in one critical training service/workspace.
- Expand to additional workspaces after stable score trends.