gpt-5.6-sol
nano-gpt-data-curation — graded by the task's verifier against a measured baseline.
- backend
- modal
- variant
- codex azure_ai/gpt-5.6-sol
- metric
- held-out multi-domain perplexity
- actions
- 304
- duration
- 1h 26m
- recorded
- 2026-08-03
run iddclm-nano-curation__4yt6SE3
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\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
Script completed
Wall time 10.0 seconds
Output:
{"chunk_id":"d19be1","wall_time_seconds":10.002383407,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"bbb9c4","wall_time_seconds":10.000623121,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
Script completed
Wall time 10.0 seconds
Output:
{"chunk_id":"f5b078","wall_time_seconds":10.000935756,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
Script completed
Wall time 10.0 seconds
Output:
{"chunk_id":"0a832c","wall_time_seconds":10.002177328,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"d8028b","wall_time_seconds":10.001591141,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"3c9a29","wall_time_seconds":10.001253638,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
Script completed
Wall time 10.0 seconds
Output:
{"chunk_id":"0a3daf","wall_time_seconds":10.001679004,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"7246f4","wall_time_seconds":10.001192568,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
Script completed
Wall time 10.0 seconds
Output:
{"chunk_id":"e15232","wall_time_seconds":10.000533338,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"0c93fe","wall_time_seconds":10.002542337,"session_id":97655,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"33376f","wall_time_seconds":10.001589001,"session_id":97655,"original_token_count":46,"output":"Token indices sequence length is longer than the specified maximum sequence length for this model (5414 > 1024). Running this sequence through the model will result in indexing errors\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":97655,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Output:
{"chunk_id":"be3b8a","wall_time_seconds":0.00000311,"exit_code":0,"original_token_count":39,"output":"{\"documents\": 13540, \"planned_tokens\": 12500214, \"tokens_by_domain\": {\"encyclopedic\": 3125121, \"web\": 3124897, \"news\": 3124937, \"technical_qa\": 3125259}}\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({\"cmd\":\"bash dev_eval.sh /tmp/candidate8_selection.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":3000});\ntext(r.output);\nif (r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}exec result
Script completed
Wall time 1.2 seconds
Output:
SESSION_ID=93403encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":93403,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"229004","wall_time_seconds":10.001703484,"session_id":93403,"original_token_count":46,"output":"Token indices sequence length is longer than the specified maximum sequence length for this model (5414 > 1024). Running this sequence through the model will result in indexing errors\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":93403,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Output:
{"chunk_id":"d4a1dc","wall_time_seconds":10.002176606,"session_id":93403,"original_token_count":15,"output":"packed 12000000 tokens from 13540 ids -> /tmp/dev_train.npy\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":93403,\"chars\":\"\",\"yield_time_ms\":30000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
Script running with cell ID 221
Wall time 11.0 seconds
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encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "221",
"yield_time_ms": 30000,
"max_tokens": 3000
}wait result
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Wall time 3.9 seconds
Output:
{"chunk_id":"a617e5","wall_time_seconds":30.002344392,"session_id":93403,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":93403,\"chars\":\"\",\"yield_time_ms\":30000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
Script running with cell ID 222
Wall time 11.0 seconds
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encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "222",
"yield_time_ms": 30000,
"max_tokens": 3000
}wait result
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Wall time 1.6 seconds
Output:
{"chunk_id":"7b47fa","wall_time_seconds":17.050993321,"exit_code":0,"original_token_count":38,"output":"HELDOUT_PPL 335.636 loss 5.8160 train_s 55 /tmp/dev_train.npy\n(dev PPL on multi_dev; official uses a hidden disjoint sample of the same HQ domain)\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({\"cmd\":\"cat .timer/remaining_secs\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":1000});\ntext(r.output);\n"
}exec result
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Wall time 0.1 seconds
Output:
1665
Overweighting target bigrams worsened perplexity to 335.6, suggesting it favors overly generic short prose. I’ll bracket the original weight once on the lower side; after that I’ll freeze the best configuration, regenerate the deliverable with those defaults, and run exact validity/token checks.
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({\"cmd\":\"python submission/curate.py --max-chars 25000 --fluency-weight 5 --output /tmp/candidate9_selection.json --report /tmp/candidate9_report.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":3000});\ntext(r.output);\nif (r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}exec result
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Wall time 1.2 seconds
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SESSION_ID=4210encrypted chain-of-thought — recorded, not exposed
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{
"input": "const patch = \"*** Begin Patch\\n*** Add File: /workspace/claim.md\\n+# Hypothesis\\n+\\n+Under a small fixed-token budget, target-matched fluent prose with explicit token-level register balance will train a better broad English model than either random web data or a single-domain quality ranking. Long crawl pages should also be capped because a few archives, script dumps, or books otherwise consume a disproportionate share of training.\\n+\\n+# Mechanism\\n+\\n+The selection should have a higher rate of word bigrams observed repeatedly in the disclosed target, a stop-word and sentence-length distribution closer to that target, fewer navigation/commerce markers, no normalized exact duplicate pages, and many more distinct documents per 12M tokens than an uncapped ranking. Independently of final perplexity, exact GPT-2 accounting predicts approximately 3M consumed tokens from each of encyclopedic, web, news, and technical-Q&A registers.\\n+\\n+# Falsification\\n+\\n+Hold token count, training recipe, and seed fixed. Compare this selection with random data and ablations that remove register balancing, the target-bigram term, boilerplate penalties, or the document-length cap. The hypothesis is falsified if the claimed corpus diagnostics do not change in the predicted directions, or if the curated selection fails to improve perplexity consistently on disjoint broad-domain samples (ideally across several training seeds).\\n+\\n+# Transfer\\n+\\n+The method transfers to another broad English target by relearning aggregate unigram/bigram log-odds and changing the token quotas to the new target mixture; its structural noise filters remain useful for raw web data. It should not be assumed to transfer unchanged to non-English, code-dominant, dialogue-dominant, or substantially longer-context targets, where the word model, filters, length cap, and register quotas need recalibration.\\n*** End Patch\";\ntext(await tools.apply_patch(patch));\n"
}exec result
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Output:
{}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":4210,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"bca650","wall_time_seconds":10.000856841,"session_id":4210,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({\"session_id\":4210,\"chars\":\"\",\"yield_time_ms\":10000,\"max_output_tokens\":3000});\ntext(JSON.stringify(r));\n"
}exec result
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Wall time 10.0 seconds
Output:
{"chunk_id":"6b5151","wall_time_seconds":10.002897504,"session_id":4210,"original_token_count":0,"output":""}