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results/omni_finetune/OMNI_MODEL_COMPARISON.md

@@ -1,6 +1,6 @@
 # Omni Model Comparison
 
-Generated: `2026-06-12T18:14:48+00:00`
+Generated: `2026-06-13T17:41:35+00:00`
 
 Compare only rows with the same scope and target. Single-episode raw-feature metrics, 128-episode metadata baselines, Qwen3 structured JSON metrics, and the two Cosmos3 targets answer different questions: Nano future-window retrieval versus Super structured JSON Reasoner evaluation.
 
@@ -55,8 +55,8 @@ The one-episode Qwen entry is only a sensor-adapter smoke test with Qwen3 weight
 | full-param gate | passed | Full-Parameter 256-Step Post-Qwen-v6 Pilot | 2048 windows/samples | full_parameter_gate=passed, observed_train_steps=256, final_step_loss=0.0096, epoch_train_loss=0.1158, checkpoint_saved=False | `results/omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot256_after_qwen_v6_preemptible_8gpu_20260611/training_metadata.json` |
 | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=0.8750, action_macro_f1=0.0027, transition_accuracy=0.8504, contact_accuracy=0.6451 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/verified_result_summary.json` |
 | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=0.8527, action_macro_f1=0.0021, transition_accuracy=0.8281, contact_accuracy=0.6518 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_fullsplit_fast8gpu_lora_fsdp_full_train_noval_tail_logits_fullstatesave_v6_eval_test_full/verified_result_summary.json` |
-| 128 episode | verified current | Qwen3-Omni LoRA | 119 episodes, 34269 windows/samples, 4032 eval | json_validity_rate=1.0000, action_macro_f1=0.0023, transition_accuracy=0.9908, contact_accuracy=0.7865 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v5_full8gpu_lora_eval_test_full/verified_result_summary.json` |
-| 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 34269 windows/samples, 4032 eval | json_validity_rate=0.9990, action_macro_f1=0.0029, transition_accuracy=0.9898, contact_accuracy=0.8177 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v6_rank64_lr5e5_full8gpu_lora_eval_test_full/verified_result_summary.json` |
+| 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 34269 windows/samples, 4032 eval | json_validity_rate=1.0000, action_macro_f1=0.0023, transition_accuracy=0.9908, contact_accuracy=0.7865 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v5_full8gpu_lora_eval_test_full/verified_result_summary.json` |
+| 128 episode | verified current | Qwen3-Omni LoRA | 119 episodes, 34269 windows/samples, 4032 eval | json_validity_rate=0.9990, action_macro_f1=0.0029, transition_accuracy=0.9898, contact_accuracy=0.8177 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v6_rank64_lr5e5_full8gpu_lora_eval_test_full/verified_result_summary.json` |
 | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=0.9978, action_macro_f1=0.0024, transition_accuracy=0.9710, contact_accuracy=0.7188 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v2_reuse_full8gpu_lora_eval_test_full/verified_result_summary.json` |
 | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=1.0000, action_macro_f1=0.0022, transition_accuracy=0.9732, contact_accuracy=0.7210 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v3_strict_label_prompt_reuse_lora_eval_test_full/verified_result_summary.json` |
 | 128 episode | verified | Qwen3-Omni LoRA | 119 episodes, 3808 windows/samples, 448 eval | json_validity_rate=1.0000, action_macro_f1=0.0019, transition_accuracy=0.9732, contact_accuracy=0.7299 | `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v4_4epoch_full8gpu_lora_eval_test_full/verified_result_summary.json` |
@@ -132,4 +132,5 @@ This is the first verified Cosmos3-Super fine-tuned adapter branch. Its metric i
 
 ## Pending
 
-- Use the verified Qwen3 v5 dense multiscale full-eval package as the current Qwen row; older Qwen package rows remain historical diagnostics for comparison.
+- Use the verified Qwen3 v6 rank64/lr5e-5 dense multiscale full-eval package as the latest current Qwen row; the v5 release tag remains pinned as the previous verified release.
+- Read results/omni_finetune/QWEN3_V5_V6_COMPARISON_20260614.md before claiming v6 is globally better than v5, because v6 improves action macro-F1 and contact accuracy but regresses subtask, next-action, object micro-F1, and JSON validity slightly.

results/omni_finetune/QWEN3_FULL_PARAMETER_GATES_20260609.md

@@ -1,6 +1,6 @@
 # Qwen3-Omni Full-Parameter Feasibility Gates
 
-Generated: `2026-06-12T18:14:48+00:00`
+Generated: `2026-06-13T17:41:13+00:00`
 
 The 2026-06-09 gates prove that Qwen3-Omni full-parameter FSDP can load, prepare, run backward/optimizer steps, and complete guarded pilots up to 128 optimizer steps on an 8-GPU remote worker. They do not prove a production full-parameter fine-tune, and they intentionally save no full checkpoints or public weights.
 

results/omni_finetune/QWEN3_V5_V6_COMPARISON_20260614.md

@@ -0,0 +1,31 @@
+# Qwen3-Omni v5/v6 Verified Comparison
+
+Generated: `2026-06-14`
+
+This compares only the two dense multiscale Qwen3-Omni LoRA held-out packages on the same selected 128-episode setup. Both use 4,032 held-out test predictions from 14 exported test episodes.
+
+| metric | v5 | v6 | v6 - v5 |
+| --- | ---: | ---: | ---: |
+| JSON validity | 1.000000 | 0.999008 | -0.000992 |
+| Action macro-F1 | 0.002290 | 0.002883 | +0.000593 |
+| Subtask accuracy | 0.011194 | 0.003731 | -0.007463 |
+| Transition accuracy | 0.990823 | 0.989831 | -0.000992 |
+| Next-action accuracy | 0.053619 | 0.043053 | -0.010565 |
+| Contact accuracy | 0.786458 | 0.817708 | +0.031250 |
+| Object micro-F1 | 0.316146 | 0.306498 | -0.009648 |
+
+## Readout
+
+v6 is the latest verified Qwen3-Omni LoRA branch and should be shown as the current Qwen row in generated comparisons. It improves action macro-F1 and contact accuracy. It does not dominate v5: v5 remains stronger on exact JSON validity, subtask accuracy, transition accuracy, next-action accuracy, and object micro-F1.
+
+The public release policy is therefore:
+
+- keep `ropedia-xperience-10m-v5` pinned to the previous stable v5 commit,
+- publish v6 on `main`, GitHub Pages, HF Space, artifact dataset, and the Qwen LoRA model repo,
+- create a separate `ropedia-xperience-10m-v6` tag only as an experimental/latest-Qwen release, not by moving the v5 tag.
+
+## Sources
+
+- v5 package: `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v5_full8gpu_lora_eval_test_full/verified_result_summary.json`
+- v6 package: `results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v6_rank64_lr5e5_full8gpu_lora_eval_test_full/verified_result_summary.json`
+- machine-readable comparison: `docs/data/qwen3_v5_v6_comparison.json`