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 ↗encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"sleep 8; stat -c %y /tmp/dev.json; cat /tmp/dev.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":12000,\"max_output_tokens\":1000}); text(r.output);\n"
}exec result
Script completed
Wall time 8.1 seconds
Output:
2026-08-04 01:49:08.515885014 +0000
{"train_npy": "/tmp/dev_train.npy", "heldout_ppl": 425.4117513161653, "mean_loss": 6.053057526541074, "max_iters": 3000, "seed": 1337, "train_s": 55.5}The last narrow checks did not beat 2.40 (2.39: 428.38; 2.405: 425.41), so I’m freezing 2.40 at 422.47. The script-generated list matches the tested candidate exactly; final checks now cover compilation, ID validity, reproducibility, and exact 12M-token packing.
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python3 /workspace/pack_selection.py /workspace/submission/selection.json /tmp/final_train.npy\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1500}); text(r.output);\n"
}exec result
Script running with cell ID 122
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "122",
"yield_time_ms": 30000,
"max_tokens": 1500
}wait result
Script completed
Wall time 14.7 seconds
Output:
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
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"ps aux | rg pack_selection.py | tail -2; ls -lh /tmp/final_train.npy 2>/dev/null || true\",\"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 5017 0.0 0.0 12852 4900 ? Ss 01:50 0:00 /bin/bash -c ps aux | rg pack_selection.py | tail -2; ls -lh /tmp/final_train.npy 2>/dev/null || true
root 5019 0.0 0.0 17932 10300 ? S 01:50 0:00 rg pack_selection.py
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"sleep 3; ls -lh /tmp/final_train.npy; python3 - <<'PY'\\nimport numpy as np\\nx=np.load('/tmp/final_train.npy'); print(x.shape,x.dtype,int(x.min()),int(x.max()))\\nPY\\nwc -c /workspace/submission/selection.json /workspace/submission/curate.py /workspace/claim.md\\ngit diff --no-index /dev/null /workspace/submission/curate.py | head -20 || true\\ncat /workspace/.timer/remaining_secs\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":3000}); text(r.output);\n"
}exec result
Script completed
Wall time 3.3 seconds
Output:
-rw-r--r-- 1 root root 23M Aug 4 01:50 /tmp/final_train.npy
(12000000,) uint16 0 50256
1345019 /workspace/submission/selection.json
3268 /workspace/submission/curate.py
2172 /workspace/claim.md
1350459 total
/bin/bash: line 6: git: command not found
2987
The required deliverables are already valid and the exact pack contains 12,000,000 uint16 tokens. With time remaining, I’m running one higher-risk diagnostic: explicit equal-register balancing using four separate affinity models. It will replace the incumbent only if it clearly improves the same fixed evaluation; otherwise the validated 2.40 combined rank stays untouched.
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python3 - <<'PY'\\nimport json,re,collections,math\\nimport numpy as np\\nfrom transformers import AutoTokenizer\\nR=re.compile('[a-z]+'); T=AutoTokenizer.from_pretrained('gpt2'); a=np.load('/workspace/data/multi_dev.npy')\\ntcs=[collections.Counter(R.findall(T.decode(a[i*250000:(i+1)*250000]).lower())) for i in range(4)]\\nbc=collections.Counter(); docs=[]\\nfor line in open('/workspace/data/pool.jsonl'):\\n d=json.loads(line)\\n if d['id']<60000:\\n ws=R.findall(d['text'].lower()); bc.update(ws); docs.append((d['id'],len(d['text']),ws))\\nBN=sum(bc.values()); V=100000; lrs=[]\\nfor tc in tcs:\\n TN=sum(tc.values()); lr={}\\n for w,n in tc.items():\\n if n>=3:\\n v=math.log((n+3)/(TN+3*V))-math.log((bc.get(w,0)+3)/(BN+3*V)); lr[w]=max(-2,min(2,v))\\n lrs.append(lr)\\nrows=[]\\nfor i,n,ws in docs:\\n aff=[sum(lr.get(w,-.15) for w in ws)/max(1,len(ws)) for lr in lrs]\\n rows.append((i,n,aff))\\nfor wt in [1.5,2.0,2.4]:\\n lists=[sorted(rows,key=lambda x:x[0]/18000-wt*x[2][d]) for d in range(4)]\\n pos=[0]*4; chars=[0]*4; seen=set(); out=[]\\n while sum(chars)<70000000:\\n d=min(range(4),key=lambda z:chars[z])\\n while lists[d][pos[d]][0] in seen: pos[d]+=1\\n i,n,_=lists[d][pos[d]]; pos[d]+=1; seen.add(i); out.append(i); chars[d]+=n\\n # append combined regular ranking among unseen to guarantee coverage\\n rem=sorted(rows,key=lambda x:x[0]/18000-2.4*sum(x[2])/4)\\n out += [i for i,n,a in rem if i not in seen] + list(range(60000,182016))\\n json.dump(out,open(f'/tmp/sel_bal{wt}.json','w'))\\n print(wt,len(seen),chars,out[:12])\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":2000}); text(r.output);\n"
}exec result
Script running with cell ID 125
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "125",
"yield_time_ms": 30000,
"max_tokens": 2000
}wait result
Script completed
Wall time 14.5 seconds
Output:
1.5 22977 [17499614, 17504335, 17498149, 17498014] [2027, 1772, 1703, 12743, 6790, 1099, 2505, 4275, 3475, 3123, 3272, 1352]
2.0 23013 [17500810, 17511114, 17486035, 17503038] [2027, 1772, 1703, 12743, 6790, 1099, 12485, 3123, 4275, 3501, 3475, 3272]
2.4 23050 [17503438, 17494225, 17498956, 17504821] [2027, 1772, 1703, 12743, 6790, 1099, 12485, 3501, 4275, 3475, 3272, 3123]
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"bash /workspace/dev_eval.sh /tmp/sel_bal2.0.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=35184encrypted chain-of-thought — recorded, not exposed
args
{
"input": "let{output,...rest}=await tools.write_stdin({session_id:35184,chars:\"\",yield_time_ms:30000,max_output_tokens:1000});text(rest);text(output);\n"
}exec result
Script running with cell ID 127
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "127",
"yield_time_ms": 30000,
"max_tokens": 1000
}wait result
Script completed
Wall time 15.4 seconds
Output:
{"chunk_id":"f3b640","wall_time_seconds":30.000712176,"session_id":35184,"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
encrypted chain-of-thought — recorded, not exposed
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 128
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "128",
"yield_time_ms": 30000,
"max_tokens": 1000
}wait result
Script completed
Wall time 2.6 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"sleep 10; stat -c %y /tmp/dev.json; cat /tmp/dev.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":15000,\"max_output_tokens\":1000}); text(r.output);\n"
}exec result
Script completed
Wall time 10.1 seconds
Output:
2026-08-04 01:49:08.515885014 +0000
{"train_npy": "/tmp/dev_train.npy", "heldout_ppl": 425.4117513161653, "mean_loss": 6.053057526541074, "max_iters": 3000, "seed": 1337, "train_s": 55.5}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "let{output,...rest}=await tools.write_stdin({session_id:35184,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":"39201a","wall_time_seconds":5.001281572,"session_id":35184,"original_token_count":17}HELDOUT_PPL 436.951 loss 6.0798 train_s 55 /tmp/dev_train.npy
Explicit four-way quotas regressed to 436.95, so the combined distribution is better than forcing noisy domain assignments. I’m leaving the incumbent intact. One final transferable signal—frequent target bigram register patterns—is being tested as a small addition; it will be rejected unless it improves clearly.
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python3 - <<'PY'\\nimport json,re,collections,math\\nimport numpy as np\\nfrom transformers import AutoTokenizer\\nR=re.compile('[a-z]+'); T=AutoTokenizer.from_pretrained('gpt2'); tw=R.findall(T.decode(np.load('/workspace/data/multi_dev.npy')).lower())\\ntc=collections.Counter(zip(tw,tw[1:])); tc={k:v for k,v in tc.items() if v>=2}; bc=collections.Counter(); docs=[]\\nfor line in open('/workspace/data/pool.jsonl'):\\n d=json.loads(line)\\n if d['id']<60000:\\n ws=R.findall(d['text'].lower()); bs=list(zip(ws,ws[1:])); bc.update(x for x in bs if x in tc); docs.append((d['id'],bs))\\nTN=sum(tc.values()); BN=sum(bc.values()); V=300000\\nlr={k:max(-2,min(2,math.log((n+2)/(TN+2*V))-math.log((bc.get(k,0)+2)/(BN+2*V)))) for k,n in tc.items()}\\nbi={i:sum(lr.get(x,-.1) for x in bs)/max(1,len(bs)) for i,bs in docs}\\nuni={int(i):float(a) for i,a in (x.split() for x in open('/tmp/aff.tsv'))}\\nprint('bi range',np.percentile(list(bi.values()),[0,10,50,90,99,100]))\\nfor beta in [.25,.5,.8,1.2]:\\n rank=sorted(uni,key=lambda i:i/18000-2.4*uni[i]-beta*bi[i])\\n json.dump(rank+list(range(60000,182016)),open(f'/tmp/sel_bi{beta}.json','w'))\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1500}); text(r.output);\n"
}exec result
Script running with cell ID 131
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "131",
"yield_time_ms": 30000,
"max_tokens": 1500
}wait result
Script completed
Wall time 14.5 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"ls /tmp/sel_bi* 2>/dev/null | head\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":1000}); text(r.output);\n"
}exec result
Script completed
Wall time 0.1 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"ps aux | rg \\\"python3 -\\\" | tail -3\",\"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 5516 0.0 0.0 12852 6424 ? Ss 01:54 0:00 /bin/bash -c ps aux | rg "python3 -" | tail -3
root 5518 0.0 0.0 17932 11564 ? S 01:54 0:00 rg python3 -
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python3 - <<'PY'\\nimport json,re,collections,math\\nimport numpy as np\\nfrom transformers import AutoTokenizer\\nR=re.compile('[a-z]+'); T=AutoTokenizer.from_pretrained('gpt2'); tw=R.findall(T.decode(np.load('/workspace/data/multi_dev.npy')).lower())\\ntc0=collections.Counter(zip(tw,tw[1:])); tc={k:v for k,v in tc0.items() if v>=2}; bc=collections.Counter()\\nfor line in open('/workspace/data/pool.jsonl'):\\n d=json.loads(line)\\n if d['id']<60000:\\n ws=R.findall(d['text'].lower())\\n for x in zip(ws,ws[1:]):\\n if x in tc: bc[x]+=1\\nTN=sum(tc.values()); BN=sum(bc.values()); V=300000\\nlr={k:max(-2,min(2,math.log((n+2)/(TN+2*V))-math.log((bc.get(k,0)+2)/(BN+2*V)))) for k,n in tc.items()}\\nbi={}\\nfor line in open('/workspace/data/pool.jsonl'):\\n d=json.loads(line)\\n if d['id']<60000:\\n ws=R.findall(d['text'].lower()); total=0.; n=0\\n for x in zip(ws,ws[1:]): total+=lr.get(x,-.1); n+=1\\n bi[d['id']]=total/max(1,n)\\nuni={int(i):float(a) for i,a in (x.split() for x in open('/tmp/aff.tsv'))}\\nfor beta in [.25,.5,.8,1.2]:\\n rank=sorted(uni,key=lambda i:i/18000-2.4*uni[i]-beta*bi[i])\\n json.dump(rank+list(range(60000,182016)),open(f'/tmp/sel_bi{beta}.json','w'))\\nprint(len(tc),len(lr),min(bi.values()),max(bi.values()))\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1000}); text(r.output);\n"
}exec result
Script running with cell ID 134
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "134",
"yield_time_ms": 30000,
"max_tokens": 1000
}wait result
Script completed
Wall time 15.6 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"ps aux | rg \\\"python3 -\\\" | tail -3; ls /tmp/sel_bi* 2>/dev/null | head\",\"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 5535 98.3 0.4 5347872 4733144 ? Rl 01:54 0:33 python3 -
root 5597 0.0 0.0 12852 5312 ? Ss 01:55 0:00 /bin/bash -c ps aux | rg "python3 -" | tail -3; ls /tmp/sel_bi* 2>/dev/null | head
root 5599 0.0 0.0 17932 9968 ? S 01:55 0:00 rg python3 -
/tmp/sel_bi0.25.json
/tmp/sel_bi0.5.json
/tmp/sel_bi0.8.json
/tmp/sel_bi1.2.json
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"bash /workspace/dev_eval.sh /tmp/sel_bi0.25.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=89499