gpt-5.6-sol
on-policy-self-distillation — graded by the task's verifier against a measured baseline.
- backend
- modal
- variant
- codex azure_ai/gpt-5.6-sol
- metric
- AIME24 avg@12 accuracy
- actions
- 596
- duration
- 7h 59m
- recorded
- 2026-08-03
run idopsd-aime24-4gpus__kuc95M7
Everything gpt-5.6-sol did on this task, in order.
download JSON ↗encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r=await tools.write_stdin({session_id:67176,chars:\"\",yield_time_ms:60000,max_output_tokens:300}); text(r.output.slice(-600));\n"
}exec result
Script running with cell ID 322
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "322",
"yield_time_ms": 60000,
"max_tokens": 300
}wait result
Script completed
Wall time 46.5 seconds
Output:
Processed prompts: 57%|█████▋ | 48/84 [10:06<05:58, 9.96s/it, est. speed input: 6.67 toks/s, output: 1086.39 toks/s]encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r=await tools.write_stdin({session_id:67176,chars:\"\",yield_time_ms:60000,max_output_tokens:300}); text(r.output.slice(-600));\n"
}exec result
Script running with cell ID 323
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "323",
"yield_time_ms": 60000,
"max_tokens": 300
}wait result
Script completed
Wall time 46.3 seconds
Output:
Processed prompts: 71%|███████▏ | 60/84 [10:25<02:46, 6.92s/it, est. speed input: 9.06 toks/s, output: 1453.62 toks/s]
Processed prompts: 50%|█████ | 48/96 [10:55<10:58, 13.71s/it, est. speed input: 8.82 toks/s, output: 775.66 toks/s]
Processed prompts: 62%|██████▎ | 60/96 [11:12<05:34, 9.28s/it, est. speed input: 10.75 toks/s, output: 1024.03 toks/s]encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r=await tools.write_stdin({session_id:67176,chars:\"\",yield_time_ms:60000,max_output_tokens:300}); text(r.output.slice(-600));\n"
}exec result
Script running with cell ID 324
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "324",
"yield_time_ms": 60000,
"max_tokens": 300
}wait result
Script completed
Wall time 18.0 seconds
Output:
rocessed prompts: 88%|████████▊ | 84/96 [11:…74 tokens truncated…nput: 1.40 toks/s, output: 252.73 toks/s]
Processed prompts: 29%|██▊ | 24/84 [12:01<24:46, 24.78s/it, est. speed input: 3.18 toks/s, output: 534.59 toks/s]
Processed prompts: 100%|██████████| 84/84 [12:10<00:00, 5.32s/it, est. speed input: 11.97 toks/s, output: 2069.11 toks/s]
Processed prompts: 100%|██████████| 84/84 [12:10<00:00, 5.32s/it, est. speed input: 11.97 toks/s, output: 2069.11 toks/s]
Processed prompts: 100%|██████████| 84/84 [12:10<00:00, 8.69s/it, est. speed input: 11.97 toks/s, output: 2069.11 toks/s]
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r=await tools.write_stdin({session_id:67176,chars:\"\",yield_time_ms:60000,max_output_tokens:300}); text(r.output.slice(-600));\n"
}exec result
Script running with cell ID 325
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "325",
"yield_time_ms": 60000,
"max_tokens": 300
}wait result
Script completed
Wall time 45.1 seconds
Output:
mpts: 71%|███████▏ | 60/84 [12:54<02:31, 6.30s/it, est. speed input: 7.90 toks/s, output: 1503.99 toks/s]
Processed prompts: 100%|██████████| 96/96 [12:55<00:00, 5.15s/it, est. speed input: 19.58 toks/s, output: 2115.12 toks/s]
Processed prompts: 100%|██████████| 96/96 [12:55<00:00, 5.15s/it, est. speed input: 19.58 toks/s, output: 2115.12 toks/s]
Processed prompts: 100%|██████████| 96/96 [12:55<00:00, 8.08s/it, est. speed input: 19.58 toks/s, output: 2115.12 toks/s]
Processed prompts: 86%|████████▌ | 72/84 [13:22<00:59, 4.95s/it, est. speed input: 9.10 toks/s, output: 1819.73 toks/s]encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r=await tools.write_stdin({session_id:67176,chars:\"\",yield_time_ms:60000,max_output_tokens:300}); text(r.output.slice(-600));\n"
}exec result
Script running with cell ID 326
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "326",
"yield_time_ms": 60000,
"max_tokens": 300
}wait result
Script completed
Wall time 44.7 seconds
Output:
Processed prompts: 62%|██████▎ | 60/96 [13:45<05:41, 9.48s/it, est. speed input: 9.82 toks/s, output: 1319.04 toks/s]
Processed prompts: 100%|██████████| 84/84 [14:09<00:00, 4.59s/it, est. speed input: 11.72 toks/s, output: 2082.08 toks/s]
Processed prompts: 100%|██████████| 84/84 [14:09<00:00, 4.59s/it, est. speed input: 11.72 toks/s, output: 2082.08 toks/s]
Processed prompts: 100%|██████████| 84/84 [14:09<00:00, 10.11s/it, est. speed input: 11.72 toks/s, output: 2082.08 toks/s]
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r=await tools.write_stdin({session_id:67176,chars:\"\",yield_time_ms:60000,max_output_tokens:300}); text(r.output.slice(-600));\n"
}exec result
Script running with cell ID 327
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "327",
"yield_time_ms": 60000,
"max_tokens": 300
}wait result
Script completed
Wall time 22.5 seconds
Output:
| 84/96 [14:28<01:00, 5.03s/it, est. speed input: 12.64 toks/s, output: 1895.19 toks/s]
Processed prompts: 100%|██████████| 96/96 [15:08<00:00, 4.49s/it, est. speed input: 14.40 toks/s, output: 2164.32 toks/s]
Processed prompts: 100%|██████████| 96/96 [15:08<00:00, 4.49s/it, est. speed input: 14.40 toks/s, output: 2164.32 toks/s]
Processed prompts: 100%|██████████| 96/96 [15:08<00:00, 9.46s/it, est. speed input: 14.40 toks/s, output: 2164.32 toks/s]
FINAL avg@12 accuracy: 50.83% (183/360 solutions correct on 30 problems)
Results written to /workspace/eval_results/dev_eval_1785749670.json
The higher-rate candidate scored 50.83% (183/360), a clear regression. I’m removing that override and finalizing the replicated 5e-6 method: two independent final-method runs scored 56.11%, and the reduction-control run also landed at 56.11%.
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const patch = \"*** Begin Patch\\n*** Update File: /workspace/submission/recipe.env\\n@@\\n-learning_rate=7.5e-6\\n+# learning_rate=5e-6\\n*** End Patch\";\ntext(await tools.apply_patch(patch));\n"
}exec result
Script completed
Wall time 0.0 seconds
Output:
{}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.update_plan({explanation:\"Implemented and benchmarked normalized front-loaded trajectory credit assignment; rejected data, scheduler, clipping, slope, trajectory-reduction, and learning-rate variants that did not improve robustly.\",\"plan\":[{\"step\":\"Inspect the OPSD implementation, paper, baseline recipe, and logs\",\"status\":\"completed\"},{\"step\":\"Design and implement a budget-neutral method improvement\",\"status\":\"completed\"},{\"step\":\"Run capped training and full AIME24 evaluations across controlled variants\",\"status\":\"completed\"},{\"step\":\"Restore the strongest replicated candidate and verify the submission\",\"status\":\"in_progress\"}]}); text(r);\n"
}exec result
Script completed
Wall time 0.0 seconds
Output:
{}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport torch\\nfrom opsd_trainer import OPSDTrainer\\nstudent = torch.randn(2, 4, 11, requires_grad=True)\\nteacher = torch.randn(2, 4, 11)\\nlabels = torch.tensor([[1, 2, 3, 4], [1, 2, -100, -100]])\\nloss = OPSDTrainer.generalized_jsd_loss(\\n student, teacher, labels=labels, beta=0, temperature=1.1,\\n reduction='batchmean', token_clip=0.05,\\n)\\nloss.backward()\\nassert loss.ndim == 0 and torch.isfinite(loss)\\nassert student.grad is not None and torch.isfinite(student.grad).all()\\nprint(f'direct loss/gradient smoke test passed: loss={loss.item():.6f}')\\nPY\\npython -m py_compile opsd_train.py opsd_trainer.py data_collator.py\\nif awk 'NF && $1 !~ /^#/' /workspace/submission/recipe.env | grep -q .; then echo 'ERROR: active recipe overrides remain'; exit 1; else echo 'recipe.env: no active overrides'; fi\\ngit diff --check -- opsd_trainer.py\\ngit diff --stat -- opsd_trainer.py\\ngit status --short\\ncat /workspace/.timer/remaining_secs\",workdir:\"/workspace/repo\",yield_time_ms:30000,max_output_tokens:4000}); text(r.output);\n"
}exec result
Script running with cell ID 330
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "330",
"yield_time_ms": 30000,
"max_tokens": 4000
}wait result
Script completed
Wall time 0.0 seconds
Output:
/workspace/repo/opsd_trainer.py:63: TRLExperimentalWarning: You are importing from 'trl.experimental'. APIs here are unstable and may change or be removed without notice. Silence this warning by setting environment variable TRL_EXPERIMENTAL_SILENCE=1.
from trl.experimental.gold.gold_config import GOLDConfig
direct loss/gradient smoke test passed: loss=-0.018829
recipe.env: no active overrides
opsd_trainer.py | 26 +++++++++++++++++++++-----
1 file changed, 21 insertions(+), 5 deletions(-)
M README.md
M opsd_trainer.py
2780
Final verification passed: the production loss has finite gradients, the weighting preserves exactly unit average credit per nonempty trajectory, syntax compiles, and recipe.env has no active override. The unrelated pre-existing README modification remains untouched.
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.update_plan({explanation:\"Restored the replicated 5e-6 candidate, removed all recipe overrides, and completed syntax, invariant, gradient, diff, and submission checks.\",\"plan\":[{\"step\":\"Inspect the OPSD implementation, paper, baseline recipe, and logs\",\"status\":\"completed\"},{\"step\":\"Design and implement a budget-neutral method improvement\",\"status\":\"completed\"},{\"step\":\"Run capped training and full AIME24 evaluations across controlled variants\",\"status\":\"completed\"},{\"step\":\"Restore the strongest replicated candidate and verify the submission\",\"status\":\"completed\"}]}); text(r);\n"
}exec result
Script completed
Wall time 0.0 seconds
Output:
{}Implemented normalized front-loaded OPSD credit assignment in opsd_trainer.py.
- Token weights decay linearly from 1.5 to 0.5 across each rollout.
- Mean weight remains exactly 1, preserving loss scale and budget.
- Two independent full dev runs scored 56.11% versus the 54.22% baseline: +1.89 points.
- recipe.env has no active overrides.
- Syntax, weighting invariants, and gradient checks pass.
- Pre-existing README changes were untouched.