nano-gpt-data-curation

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: 202
duration: 53m
recorded: 2026-08-04

run iddclm-nano-curation__KgMs7QW

Everything gpt-5.6-sol did on this task, in order.

download JSON ↗

codexgpt-5.6-sol219 turns17 narration202 reasoning202 action202 observation1 final

#126

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "87",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}

wait result

Script completed
Wall time 7.5 seconds
Output:

#127

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "let{output,...rest}=await tools.write_stdin({session_id:7236,chars:\"\",yield_time_ms:1000,max_output_tokens:1000});text(rest);text(output);\n"
}

exec result

Script completed
Wall time 0.0 seconds
Output:
{"chunk_id":"4469ea","wall_time_seconds":0.000003007,"exit_code":0,"original_token_count":38}HELDOUT_PPL 422.468  loss 6.0461  train_s 55  /tmp/dev_train.npy
(dev PPL on multi_dev; official uses a hidden disjoint sample of the same HQ domain)

#128

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"bash /workspace/dev_eval.sh /tmp/sel_aff2.6.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":1000}); text(r.output); if(r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}

exec result

Script completed
Wall time 1.2 seconds
Output:
SESSION_ID=97794

#129

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const patch = \"*** Begin Patch\\n*** Delete File: /workspace/submission/curate.py\\n*** Add File: /workspace/submission/curate.py\\n+#!/usr/bin/env python3\\n+\\\"\\\"\\\"Curate with regularized target/corpus word log-odds (Moore-Lewis style).\\n+\\n+The disclosed multi-domain dev set supplies the desired lexical/register\\n+distribution, not labels for individual pool documents.  Per-word evidence is\\n+smoothed and clipped, then combined with the pool's strong monotone assembly\\n+quality rank.  This regularization keeps isolated topical matches from pulling\\n+spam or boilerplate out of the low-quality tail.\\n+\\\"\\\"\\\"\\n+import argparse\\n+import collections\\n+import json\\n+import math\\n+import re\\n+from pathlib import Path\\n+\\n+import numpy as np\\n+from transformers import AutoTokenizer\\n+\\n+WORD_RE = re.compile(r\\\"[a-z]+\\\")\\n+CANDIDATE_ID_LIMIT = 60_000\\n+RANK_SCALE = 18_000.0\\n+AFFINITY_WEIGHT = 2.4\\n+SMOOTHING = 3.0\\n+VOCAB_PRIOR = 100_000\\n+MIN_TARGET_COUNT = 3\\n+UNKNOWN_LOG_ODDS = -0.15\\n+LOG_ODDS_CLIP = 2.0\\n+\\n+\\n+def words(text):\\n+    return WORD_RE.findall(text.lower())\\n+\\n+\\n+def main():\\n+    ap = argparse.ArgumentParser()\\n+    ap.add_argument(\\\"--pool\\\", default=\\\"/workspace/data/pool.jsonl\\\")\\n+    ap.add_argument(\\\"--dev\\\", default=\\\"/workspace/data/multi_dev.npy\\\")\\n+    ap.add_argument(\\\"--output\\\", default=\\\"/workspace/submission/selection.json\\\")\\n+    args = ap.parse_args()\\n+\\n+    tokenizer = AutoTokenizer.from_pretrained(\\\"gpt2\\\")\\n+    target_text = tokenizer.decode(np.load(args.dev))\\n+    target_counts = collections.Counter(words(target_text))\\n+\\n+    # Estimate the competing web distribution from the only region that the\\n+    # regularized rank can realistically select. This is faster and avoids\\n+    # letting the obvious junk tail define what \\\"web-like\\\" means.\\n+    background_counts = collections.Counter()\\n+    with open(args.pool, encoding=\\\"utf-8\\\") as f:\\n+        for line in f:\\n+            row = json.loads(line)\\n+            if row[\\\"id\\\"] < CANDIDATE_ID_LIMIT:\\n+                background_counts.update(words(row[\\\"text\\\"]))\\n+\\n+    nt = sum(target_counts.values())\\n+    nb = sum(background_counts.values())\\n+    target_denom = nt + SMOOTHING * VOCAB_PRIOR\\n+    background_denom = nb + SMOOTHING * VOCAB_PRIOR\\n+    log_odds = {}\\n+    for word, count in target_counts.items():\\n+        if count < MIN_TARGET_COUNT:\\n+            continue\\n+        value = (math.log((count + SMOOTHING) / target_denom)\\n+                 - math.log((background_counts.get(word, 0) + SMOOTHING)\\n+                            / background_denom))\\n+        log_odds[word] = max(-LOG_ODDS_CLIP, min(LOG_ODDS_CLIP, value))\\n+\\n+    ranked, tail = [], []\\n+    with open(args.pool, encoding=\\\"utf-8\\\") as f:\\n+        for line in f:\\n+            row = json.loads(line)\\n+            doc_id = row[\\\"id\\\"]\\n+            if doc_id >= CANDIDATE_ID_LIMIT:\\n+                tail.append(doc_id)\\n+                continue\\n+            doc_words = words(row[\\\"text\\\"])\\n+            affinity = sum(log_odds.get(w, UNKNOWN_LOG_ODDS)\\n+                           for w in doc_words) / max(1, len(doc_words))\\n+            priority = doc_id / RANK_SCALE - AFFINITY_WEIGHT * affinity\\n+            ranked.append((priority, doc_id))\\n+\\n+    ranked.sort(key=lambda item: (item[0], item[1]))\\n+    tail.sort()\\n+    selection = [doc_id for _, doc_id in ranked] + tail\\n+    Path(args.output).parent.mkdir(parents=True, exist_ok=True)\\n+    with open(args.output, \\\"w\\\") as f:\\n+        json.dump(selection, f)\\n+        f.write(\\\"\\\\n\\\")\\n+\\n+\\n+if __name__ == \\\"__main__\\\":\\n+    main()\\n*** End Patch\";\ntext(await tools.apply_patch(patch));\n"
}

exec result

Script completed
Wall time 0.0 seconds
Output:
{}

#130

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "let{output,...rest}=await tools.write_stdin({session_id:97794,chars:\"\",yield_time_ms:30000,max_output_tokens:1000});text(rest);text(output);\n"
}

exec result

Script running with cell ID 91
Wall time 11.0 seconds
Output:

#131

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "91",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}

wait result

Script completed
Wall time 15.7 seconds
Output:
{"chunk_id":"b6af1f","wall_time_seconds":30.001669484,"session_id":97794,"original_token_count":62}Token indices sequence length is longer than the specified maximum sequence length for this model (1043 > 1024). Running this sequence through the model will result in indexing errors
packed 12000000 tokens from 182016 ids -> /tmp/dev_train.npy

#132

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"sleep 60; cat /tmp/dev.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1000}); text(r.output);\n"
}

exec result

Script running with cell ID 92
Wall time 11.0 seconds
Output:

#133

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "92",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}

wait result

Script completed
Wall time 8.4 seconds
Output:

#134

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "let{output,...rest}=await tools.write_stdin({session_id:97794,chars:\"\",yield_time_ms:1000,max_output_tokens:1000});text(rest);text(output);\n"
}

exec result

Script completed
Wall time 0.0 seconds
Output:
{"chunk_id":"0e88ef","wall_time_seconds":0.000003343,"exit_code":0,"original_token_count":38}HELDOUT_PPL 443.618  loss 6.0950  train_s 55  /tmp/dev_train.npy
(dev PPL on multi_dev; official uses a hidden disjoint sample of the same HQ domain)

#135

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"bash /workspace/dev_eval.sh /tmp/sel_aff2.2.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":1000}); text(r.output); if(r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}

exec result

Script completed
Wall time 1.2 seconds
Output:
SESSION_ID=82851

#136

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"python3 - <<'PY'\\nimport json\\nrows=[(int(i),float(a)) for i,a in (x.split() for x in open('/tmp/aff.tsv'))]\\nfor lam in [2.3,2.35,2.45,2.5]:\\n rank=sorted(rows,key=lambda x:x[0]/18000-lam*x[1])\\n json.dump([i for i,a in rank]+list(range(60000,182016)),open(f'/tmp/sel_aff{lam}.json','w'))\\nPY\\ncat /workspace/.timer/remaining_secs\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":1000}); text(r.output);\n"
}

exec result

Script completed
Wall time 0.5 seconds
Output:
3688

#137

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "let{output,...rest}=await tools.write_stdin({session_id:82851,chars:\"\",yield_time_ms:30000,max_output_tokens:1000});text(rest);text(output);\n"
}

exec result

Script running with cell ID 96
Wall time 11.0 seconds
Output:

#138

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "96",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}

wait result

Script completed
Wall time 13.7 seconds
Output:
{"chunk_id":"25927d","wall_time_seconds":30.001359788,"session_id":82851,"original_token_count":62}Token indices sequence length is longer than the specified maximum sequence length for this model (1043 > 1024). Running this sequence through the model will result in indexing errors
packed 12000000 tokens from 182016 ids -> /tmp/dev_train.npy

#139

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"sleep 60; stat -c %y /tmp/dev.json; cat /tmp/dev.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1000}); text(r.output);\n"
}

exec result

Script running with cell ID 97
Wall time 11.0 seconds
Output:

#140

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "97",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}

wait result

Script completed
Wall time 10.6 seconds
Output:

#141

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "let{output,...rest}=await tools.write_stdin({session_id:82851,chars:\"\",yield_time_ms:1000,max_output_tokens:1000});text(rest);text(output);\n"
}

exec result

Script completed
Wall time 5.0 seconds
Output:
{"chunk_id":"1e3630","wall_time_seconds":5.000976468,"session_id":82851,"original_token_count":0}

#142

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"ps aux | rg train_nano.py | tail -2; stat -c %y /tmp/dev.json; cat /tmp/dev.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":1000}); text(r.output);\n"
}

exec result

Script completed
Wall time 0.1 seconds
Output:
root      3932  0.0  0.0  12852  5280 ?        Ss   01:40   0:00 /bin/bash -c ps aux | rg train_nano.py | tail -2; stat -c %y /tmp/dev.json; cat /tmp/dev.json
root      3934  0.0  0.0  17932 11460 ?        S    01:40   0:00 rg train_nano.py
2026-08-04 01:40:38.814188591 +0000
{"train_npy": "/tmp/dev_train.npy", "heldout_ppl": 440.32171841976924, "mean_loss": 6.087505637958485, "max_iters": 3000, "seed": 1337, "train_s": 55.7}

#143

narration

The bracket is sharp: 2.2 gives 440.32 and 2.6 gives 443.62, versus 422.47 at 2.4. I’m checking a close neighbor to make sure the 2.4 result is reproducible as a ranking optimum rather than a bookkeeping issue, then I’ll freeze the criterion and validate the generated deliverables.

#144

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"bash /workspace/dev_eval.sh /tmp/sel_aff2.35.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":1000}); text(r.output); if(r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}

exec result

Script completed
Wall time 1.2 seconds
Output:
SESSION_ID=32441

#145

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "let{output,...rest}=await tools.write_stdin({session_id:32441,chars:\"\",yield_time_ms:30000,max_output_tokens:1000});text(rest);text(output);\n"
}

exec result

Script running with cell ID 101
Wall time 11.0 seconds
Output:

#146

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "101",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}

wait result

Script completed
Wall time 8.4 seconds
Output:
{"chunk_id":"06baf8","wall_time_seconds":30.002141528,"session_id":32441,"original_token_count":62}Token indices sequence length is longer than the specified maximum sequence length for this model (1043 > 1024). Running this sequence through the model will result in indexing errors
packed 12000000 tokens from 182016 ids -> /tmp/dev_train.npy

#147

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"sleep 60; stat -c %y /tmp/dev.json; cat /tmp/dev.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1000}); text(r.output);\n"
}

exec result

Script running with cell ID 102
Wall time 11.0 seconds
Output:

#148

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "102",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}

wait result

Script completed
Wall time 8.5 seconds
Output:

#149

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"ps aux | rg train_nano.py | tail -2; stat -c %y /tmp/dev.json; cat /tmp/dev.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":1000}); text(r.output);\n"
}

exec result

Script completed
Wall time 0.1 seconds
Output:
root      4115  0.0  0.0  12852  4884 ?        Ss   01:42   0:00 /bin/bash -c ps aux | rg train_nano.py | tail -2; stat -c %y /tmp/dev.json; cat /tmp/dev.json
root      4117  0.0  0.0  17932 11624 ?        S    01:42   0:00 rg train_nano.py
2026-08-04 01:40:38.814188591 +0000
{"train_npy": "/tmp/dev_train.npy", "heldout_ppl": 440.32171841976924, "mean_loss": 6.087505637958485, "max_iters": 3000, "seed": 1337, "train_s": 55.7}

#150

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "let{output,...rest}=await tools.write_stdin({session_id:32441,chars:\"\",yield_time_ms:1000,max_output_tokens:1000});text(rest);text(output);\n"
}

exec result

Script completed
Wall time 5.0 seconds
Output:
{"chunk_id":"23ca68","wall_time_seconds":5.00067746,"session_id":32441,"original_token_count":0}