LoRA-SFT PubMedQA grader vs untuned Qwen3.5-4B judge
Succeeded
weak evidence for
Devin
Qwen/Qwen3.5-4B
SFT
1.5 GPU-h budget
started 1d ago
1h 13m
Rank-32 LoRA SFT of Qwen/Qwen3.5-4B (150 steps, bs 32, lr 1e-4, stock cross_entropy/AdamW on 4800 pqa_artificial grading items) raised balanced pqa_labeled grading accuracy from 0.7185 (untuned) to 0.8335 on the same 2000 items under one frozen evaluator. Paired difference 0.1150 with Hoeffding 95% interval [0.0543, 0.1757]; the lower bound exceeds the 0.03 margin, so the hypothesis is supported.
Why
The agent judged the hypothesis supported; no effect size was recorded against the margin. Confidence is limited by: decision evidence unverified; feasibility evidence incomplete. Reclassified from inconclusive under the direction-plus-confidence rule.
Result accuracy_gold_maybe
base mean 0.4568 · 2 armslora mean 0.1727 · 1 arm
| arm | accuracy_gold_maybe | accuracy | predicted_correct_fraction | n |
|---|---|---|---|---|
| base_untuned | 0.4545 | 0.7185 | 0.6075 | 2,000 |
| base_untuned_attempt1_evaluator_4bf3ad01 | 0.4591 | 0.7205 | 0.6065 | 2,000 |
| lora_sft_grader | 0.1727 | 0.8335 | 0.4985 | 2,000 |
Changes from the spec 0
Original hypothesis tested: yes
Checks · activation passed · evaluator comparable · feasibility unknown
Custom implementation correctness: not_applicable
experiment_features: custom_loss, custom_optimizer is false
Validates executor-reported evidence; autonomous training calls are not blocked by this server.
Treatment activation: passed
Every activation check is within its prespecified range.
- executed_base_model
- Qwen/Qwen3.5-4B needs one of Qwen/Qwen3.5-4B · passed
- eval_correct_label_fraction
- 0.5 needs >= 0.49 and <= 0.51 · passed
- train_eval_pmid_overlap
- 0 needs >= 0 and <= 0 · passed
- verdict_token_loss_drop_pilot
- 0.9990810224589662 needs >= 0.1 · passed
- base_predicted_correct_fraction
- 0.6 needs >= 0.05 and <= 0.95 · passed
Initialization / optimizer verification: not applicable
experiment_features: paired_training_arms, checkpoint_restore is false
Research decision: unverified
Observation file name/hash is not retained for this run.
Evaluator comparability: comparable
accuracy: comparable · baseline, treatment
Evaluator identities and per-arm scores
{
"comparisons": [
{
"arms": [
"baseline",
"treatment"
],
"metric": "accuracy"
}
],
"evaluators": {
"25131a53fcdc110273727c96f2ec27d2ee549f02068efac718bed9e09fc9cbae": {
"code_sha256": "b1fed5101db396040622ed2181e2752107f1465f8649620caec32dce257e9b97",
"decoding": {
"max_tokens": 0,
"method": "forced-completion summed logprob via SamplingClient.compute_logprobs",
"stop": [],
"temperature": 0
},
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"pqa_labeled:16564683:INCORRECT",
"pqa_labeled:23147106:CORRECT",
"pqa_labeled:23147106:INCORRECT",
"pqa_labeled:21550158:CORRECT",
"pqa_labeled:21550158:INCORRECT",
"pqa_labeled:17559449:CORRECT",
"pqa_labeled:17559449:INCORRECT"
]
},
"parser": "prediction = 'CORRECT' if sum(logprobs[CORRECT tokens]) > sum(logprobs[INCORRECT tokens]) else 'INCORRECT'; value = int(prediction == gold label)",
"prompt_template": {
"completions": {
"CORRECT": [
50564,
43347
],
"INCORRECT": [
37163,
842,
43347
]
},
"deps": {
"datasets": "5.1.0",
"tinker": "0.37.0",
"tinker-cookbook": "0.5.9",
"torch": "2.15.0",
"transformers": "5.22.1"
},
"max_seq_len": 1024,
"renderer": "tinker_cookbook renderers.get_renderer('qwen3', get_tokenizer('Qwen/Qwen3.5-4B')).build_generation_prompt([user]) (no system prompt; ends '<|im_start|>assistant\\n')",
"user": "Context: {context}\nQuestion: {question}\nCandidate answer: {candidate}\nIs the candidate answer correct? Reply CORRECT or INCORRECT."
}
}
},
"scores": [
{
"arm": "baseline",
"evaluator_id": "25131a53fcdc110273727c96f2ec27d2ee549f02068efac718bed9e09fc9cbae",
"metric": "accuracy",
"predictions_ref": "predictions_base_untuned.jsonl",
"seed": 0,
"value": 0.7185
},
{
"arm": "treatment",
"evaluator_id": "25131a53fcdc110273727c96f2ec27d2ee549f02068efac718bed9e09fc9cbae",
"metric": "accuracy",
"predictions_ref": "predictions_lora_sft_grader.jsonl",
"seed": 0,
"value": 0.8335
}
],
"version": 1
}Feasibility projection: unknown
- Projected wall time
- unknown
- Projected GPU allocation
- unknown
- Re-projection required: dataset changed or was not recorded
- Re-projection required: steps changed or was not recorded
- Re-projection required: n_examples changed or was not recorded
- Re-projection required: n_eval changed or was not recorded
Timing, sample counts and allocation evidence
{
"generation_applicability": {
"check": "generation_audit",
"enforce": false,
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},
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"Re-projection required: steps changed or was not recorded",
"Re-projection required: n_examples changed or was not recorded",
"Re-projection required: n_eval changed or was not recorded"
],
"record": {
"config": {
"arms": [
"base_untuned",
"lora_sft_grader"
],
"base_model": "Qwen/Qwen3.5-4B",
"batch_size": 32,
"lora_rank": 32,
"lr": 0.0001,
"max_seq_len": 1024,
"n_eval": 200,
"steps": 20
},
"effective_config": {
"arms": [
"base_untuned",
"lora_sft_grader"
],
"base_model": "Qwen/Qwen3.5-4B",
"batch_size": 32,
"lora_rank": 32,
"lr": 0.0001,
"max_seq_len": 1024,
"n_eval": 2000,
"steps": 150
},
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"measurements": {
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"samples": 4000,
"seconds": 261.6,
"units": 4000
},
"setup": {
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"gpu_count": null,
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"samples": 0,
"seconds": 166.9,
"units": 1
},
"training": {
"allocation_source": null,
"gpu_count": null,
"planned_units": 320,
"samples": 4800,
"seconds": 268.5,
"units": 150
}
},
"primary_endpoint": "pubmedqa_labeled_grading_accuracy",
"recovery": {
"allocation_source": null,
"gpu_count": null,
"seconds": 1800
},
"source": "pilot.json/pilot2.log (pilot); full: full_attempt2.log (base eval), treat.log (treatment train+eval)"
},
"recorded_at": 1793744733.6152964,
"status": "unknown",
"wall_seconds": null
}Generated task audit: not applicable
Spec exp_8088f9d3ee
Experiment version
exp_8088f9d3ee
Execute the selected saved experiment version.
Hypothesis
LoRA SFT on 4,800 PubMedQA-artificial grading items raises Qwen3.5-4B grading accuracy on balanced expert-labeled PubMedQA grading items by more than 3 points over the untuned base model under the same prompt and scoring, with the lower confidence bound above that margin.
Success criterion
Treatment minus baseline grading accuracy on the 2000 paired eval items exceeds 0.03, with the paired Hoeffding 95% lower bound above 0.03 (half-width about 0.06 at n=2000, so an observed gain of roughly 0.09 or more is needed). Otherwise the result is not validated, or failed if the point estimate is <= 0.
PubMedQA (pqa_artificial train, pqa_labeled eval)
150 steps
batch 32
LoRA r32
lr 0.0001
120 min wall budget
Method
Grading items are built deterministically from PubMedQA, with no model-generated data. Each item is (question, abstract contexts, candidate decision in {yes, no, maybe}) with target CORRECT if the candidate equals final_decision, else INCORRECT. Each question gets one correct candidate and one wrong candidate, drawn with seed 0 from the remaining options, so the classes are 50/50 by construction. Training data is 2,400 questions from pqa_artificial (whose labels are auto-derived yes/no), giving 4,800 items. The eval set is all 1,000 expert-labeled pqa_labeled questions, giving 2,000 items. pqa_artificial and pqa_labeled are disjoint by PMID, and this is checked. The treatment is LoRA rank 32 on Qwen/Qwen3.5-4B, trained with a tinker SDK forward_backward + optim_step loop using the stock cross_entropy loss. Loss weight sits only on the verdict tokens. AdamW at lr 1e-4, batch 32, 150 steps (about 1 epoch). The baseline is the untuned Qwen3.5-4B with the identical renderer and prompt. Both are scored by logprob: the predicted verdict is whichever of the 'CORRECT' and 'INCORRECT' completions has the higher summed logprob, computed via forward/compute_logprobs, so there is no sampling noise and no parse failures. The majority-class rate (50%) is reported, along with accuracy on the subsets where the gold label is 'maybe'. Nothing is custom server-side and there is no Spindle fork. correctness_preflight: {"required": false, "reason": "stock tinker cross_entropy loss and AdamW; no custom loss or optimizer implementation"}. Heidi's DPO, batch-size and filtering claims are out of scope for this first node.
Baseline
Untuned Qwen/Qwen3.5-4B with the same prompt, renderer, eval items and logprob scoring.
Full spec
{
"activation_gate": {
"applicable": true,
"checks": [
{
"measures": "model name reported by the created training/sampling client for both arms",
"metric": "executed_base_model",
"one_of": [
"Qwen/Qwen3.5-4B"
]
},
{
"max": 0.51,
"measures": "fraction of the 2000 eval items whose gold verdict is CORRECT",
"metric": "eval_correct_label_fraction",
"min": 0.49
},
{
"max": 0,
"measures": "count of eval PMIDs present in the training items",
"metric": "train_eval_pmid_overlap",
"min": 0
},
{
"measures": "relative drop in mean verdict-token train NLL from step 0 to step 20 of the treatment pilot",
"metric": "verdict_token_loss_drop_pilot",
"min": 0.1
},
{
"max": 0.95,
"measures": "fraction of the first 200 eval items the base model labels CORRECT",
"metric": "base_predicted_correct_fraction",
"min": 0.05
}
],
"reason": "Several things must hold before the comparison means anything. The executed model and arms must match the spec. The eval must be balanced and disjoint from training. SFT must actually move the verdict-token loss. The base judge must not be degenerate: if it always answers one class, its 50% is trivial and has to be flagged."
},
"arms": [
{
"name": "base_untuned",
"seed": 0,
"trained": false
},
{
"lr": 0.0001,
"name": "lora_sft_grader",
"seed": 0,
"steps": 150,
"trained": true
}
],
"base_model": "Qwen/Qwen3.5-4B",
"baseline": "Untuned Qwen/Qwen3.5-4B with the same prompt, renderer, eval items and logprob scoring.",
"batch_size": 32,
"budget": {
"gpu_hours": 1.5,
"max_wall_minutes": 120
},
"command": "python grader_sft.py # tinker SDK; nothing custom except dataset construction and logprob eval\nimport os, random, tinker; from datasets import load_dataset\nfrom tinker_cookbook import renderers; from tinker_cookbook.tokenizer_utils import get_tokenizer\nM='Qwen/Qwen3.5-4B'; svc=tinker.ServiceClient(base_url=os.environ['TINKER_BASE_URL'])\ntok=get_tokenizer(M); r=renderers.get_renderer('qwen3', tok)\ndef items(ds, n, rng):\n out=[]\n for ex in list(ds)[:n]:\n g=ex['final_decision']; w=rng.choice([o for o in ['yes','no','maybe'] if o!=g])\n for c,lab in [(g,'CORRECT'),(w,'INCORRECT')]:\n p=f\"Context: {' '.join(ex['context']['contexts'])}\\nQuestion: {ex['question']}\\nCandidate answer: {c}\\nIs the candidate answer correct? Reply CORRECT or INCORRECT.\"\n out.append((ex['pubid'],p,lab))\n return out\nrng=random.Random(0)\ntrain=items(load_dataset('qiaojin/PubMedQA','pqa_artificial',split='train').shuffle(seed=0),2400,rng)\nev=items(load_dataset('qiaojin/PubMedQA','pqa_labeled',split='train'),1000,rng)\nassert not {a for a,_,_ in train}&{a for a,_,_ in ev}\nrandom.Random(0).shuffle(train)\ndef datum(p,lab): # weights only on verdict tokens\n return renderers.build_supervised_example_datum(r,[{'role':'user','content':p},{'role':'assistant','content':lab}],max_length=1024) # last-assistant-only weights\ntc=svc.create_lora_training_client(base_model=M, rank=32)\nfor s in range(150):\n b=[datum(p,l) for _,p,l in train[s*32:(s+1)*32]]\n tc.forward_backward(b,'cross_entropy').result(); tc.optim_step(tinker.AdamParams(learning_rate=1e-4)).result()\nsc_t=tc.save_weights_and_get_sampling_client('pubmedqa-grader'); sc_b=svc.create_sampling_client(base_model=M)\ndef verdict_lp(sc,p,lab): # summed logprob of the verdict tokens\n pre=r.build_generation_prompt([{'role':'user','content':p}]); comp=tok.encode(lab,add_special_tokens=False)\n mi=tinker.ModelInput.from_ints(pre.to_ints()+comp); lp=sc.compute_logprobs(mi).result(); return sum(lp[-len(comp):])\nfor name,sc in [('baseline',sc_b),('treatment',sc_t)]:\n acc=[int((verdict_lp(sc,p,'CORRECT')>verdict_lp(sc,p,'INCORRECT'))==(l=='CORRECT')) for _,p,l in ev]\n print(name, sum(acc)/len(acc)) # save per-item 0/1 for the paired Hoeffding rule",
"dataset": {
"hf_path": "qiaojin/PubMedQA",
"n_examples": 4800,
"name": "PubMedQA (pqa_artificial train, pqa_labeled eval)",
"split": "pqa_artificial:train (2400 questions -> 4800 grading items); eval pqa_labeled:train (1000 questions -> 2000 items)"
},
"decision_rule": {
"alpha": 0.05,
"criteria": [
{
"bounds": [
0,
1
],
"id": "primary",
"margin": 0.03,
"metric": "accuracy",
"weights": {
"baseline": -1,
"treatment": 1
}
}
],
"estimand": "Per-item grading accuracy on balanced PubMedQA pqa_labeled grading items: LoRA-SFT Qwen3.5-4B minus untuned Qwen3.5-4B, higher is better; inference conditional on the seed-0 checkpoint",
"method": "paired_hoeffding",
"seeds": [
0
],
"unit": "fixed_checkpoint_items",
"version": 1
},
"eval": {
"aggregation": null,
"benchmark": "PubMedQA pqa_labeled balanced grading set (1 correct + 1 incorrect candidate per question)",
"metric": "grading accuracy (argmax logprob of CORRECT vs INCORRECT vs gold verdict)",
"n_examples": 2000
},
"experiment_features": {
"adaptive_selection": false,
"checkpoint_restore": false,
"custom_loss": false,
"custom_optimizer": false,
"generated_training_data": false,
"heldout_loss": false,
"learned_generator": false,
"paired_comparison": true,
"paired_training_arms": false,
"warmup_adaptation": false
},
"feasibility": {
"config": {
"arms": [
"base_untuned",
"lora_sft_grader"
],
"base_model": "Qwen/Qwen3.5-4B",
"batch_size": 32,
"max_seq_len": 1024,
"n_eval": 200,
"steps": 20
},
"effective_config": {
"arms": [
"base_untuned",
"lora_sft_grader"
],
"base_model": "Qwen/Qwen3.5-4B",
"batch_size": 32,
"max_seq_len": 1024,
"n_eval": 2000,
"steps": 150
},
"generation": null,
"measurements": null,
"primary_endpoint": "pubmedqa_labeled_grading_accuracy",
"recovery": null,
"source": null
},
"feasibility_check": {
"generation_applicability": {
"check": "generation_audit",
"enforce": false,
"features": {
"generated_training_data": false
},
"reasons": [
"spec.generation_audit opts out and no feature it covers is true"
],
"status": "not_applicable"
},
"generation_counts": null,
"gpu_hours": null,
"known_gpu_hours": 0,
"phases": {},
"problems": [
"Re-projection required: lora_rank changed or was not recorded",
"Re-projection required: dataset changed or was not recorded",
"Re-projection required: steps changed or was not recorded",
"Re-projection required: n_examples changed or was not recorded",
"Re-projection required: n_eval changed or was not recorded",
"Pilot evidence source not recorded",
"Representative setup timing not recorded",
"Representative training timing not recorded",
"Representative evaluation timing not recorded",
"Positive recovery reserve not recorded"
],
"status": "unknown",
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},
"feasibility_required": true,
"generation_audit": {
"answer_comparison": "categorical_exact",
"max_eval_overlaps": 0,
"max_label_errors": 0,
"min_sample_size": 100,
"required": false
},
"hypothesis": "LoRA SFT on 4,800 PubMedQA-artificial grading items raises Qwen3.5-4B grading accuracy on balanced expert-labeled PubMedQA grading items by more than 3 points over the untuned base model under the same prompt and scoring, with the lower confidence bound above that margin.",
"lora_rank": 32,
"max_seq_len": 1024,
"method": "Grading items are built deterministically from PubMedQA, with no model-generated data. Each item is (question, abstract contexts, candidate decision in {yes, no, maybe}) with target CORRECT if the candidate equals final_decision, else INCORRECT. Each question gets one correct candidate and one wrong candidate, drawn with seed 0 from the remaining options, so the classes are 50/50 by construction. Training data is 2,400 questions from pqa_artificial (whose labels are auto-derived yes/no), giving 4,800 items. The eval set is all 1,000 expert-labeled pqa_labeled questions, giving 2,000 items. pqa_artificial and pqa_labeled are disjoint by PMID, and this is checked. The treatment is LoRA rank 32 on Qwen/Qwen3.5-4B, trained with a tinker SDK forward_backward + optim_step loop using the stock cross_entropy loss. Loss weight sits only on the verdict tokens. AdamW at lr 1e-4, batch 32, 150 steps (about 1 epoch). The baseline is the untuned Qwen3.5-4B with the identical renderer and prompt. Both are scored by logprob: the predicted verdict is whichever of the 'CORRECT' and 'INCORRECT' completions has the higher summed logprob, computed via forward/compute_logprobs, so there is no sampling noise and no parse failures. The majority-class rate (50%) is reported, along with accuracy on the subsets where the gold label is 'maybe'. Nothing is custom server-side and there is no Spindle fork. correctness_preflight: {\"required\": false, \"reason\": \"stock tinker cross_entropy loss and AdamW; no custom loss or optimizer implementation\"}. Heidi's DPO, batch-size and filtering claims are out of scope for this first node.",
"optimizer": {
"lr": 0.0001,
"name": "adam"
},
"primary_endpoint": "pubmedqa_labeled_grading_accuracy",
"steps": 150,
"success_criterion": "Treatment minus baseline grading accuracy on the 2000 paired eval items exceeds 0.03, with the paired Hoeffding 95% lower bound above 0.03 (half-width about 0.06 at n=2000, so an observed gain of roughly 0.09 or more is needed). Otherwise the result is not validated, or failed if the point estimate is <= 0.",
"title": "LoRA-SFT PubMedQA grader vs untuned Qwen3.5-4B judge",
"training_type": "sft"
}Evidence 1
- launch-instructions-6bb4c5736124.md · instructions · 35406 bytes
Checkpoint references
[
{
"arm": "treatment",
"step": 150,
"uri": "tinker://1070692c1dfb1e531fba10227df850bd:train:0/sampler_weights/run_03530094ad-a3-final-sampler"
},
{
"arm": "treatment",
"step": 150,
"uri": "tinker://1070692c1dfb1e531fba10227df850bd/weights/run_03530094ad-a3-final"
}
]Per-arm evidence metrics
{
"baseline": {
"accuracy": 0.7185
},
"treatment": {
"accuracy": 0.8335
}
}All metrics
| metric | base_untuned | base_untuned_attempt1_evaluator_4bf3ad01 | lora_sft_grader |
|---|---|---|---|
| accuracy | 0.7185 | 0.7205 | 0.8335 |
| predicted_correct_fraction | 0.6075 | 0.6065 | 0.4985 |
| accuracy_gold_maybe | 0.4545 | 0.4591 | 0.1727 |
| n | 2,000 | 2,000 | 2,000 |
| final_train_verdict_nll | — | — | 0.001657 |
| fixed_batch_verdict_nll_end | — | — | 2.436e-05 |
- eval_correct_label_fraction
- 0.5
- train_eval_pmid_overlap
- 0
- verdict_token_loss_drop_pilot
- 0.9991
- base_predicted_correct_fraction
- 0.6
- pubmedqa_labeled_grading_accuracy_baseline
- 0.7185
- pubmedqa_labeled_grading_accuracy_treatment
- 0.8335
- accuracy_diff_treatment_minus_baseline
- 0.115
- hoeffding_lower_95
- 0.05426
- hoeffding_upper_95
- 0.1757
- margin
- 0.03
- n_eval_items
- 2,000
- treatment_train_seconds
- 268.5
- wall_minutes_total_approx
- 75
Interim updates from Devin (6, first Nov 3, 21:17 UTC)
Artifact references
- checkpoint · treatment · step 150 · tinker://1070692c1dfb1e531fba10227df850bd:train:0/sampler_weights/run_03530094ad-a3-final-sampler
- checkpoint · treatment · step 150 · tinker://1070692c1dfb1e531fba10227df850bd/weights/run_03530094ad-a3-final
- instructions · launch-instructions.md sha256 6bb4c5736124
- script · run.py sha256 cadd14a29589
- script · launch.py sha256 28dab4a506c9
- script · launch_treat.py sha256 12f1adf5877e
- script · finalize.py sha256 8673abb2c2ac
- effective_config · effective-config.json sha256 a57fd5e1ea66
- code_revision · code-revision.json sha256 82eb10a39e34
- metrics · evaluation.json sha256 d33ce1f0e1f6
- effective_config · evaluator.json sha256 eb5f479ab188
- metrics · data_stats.json sha256 c79cf76270f8
- effective_config · eval_items.jsonl sha256 2159e052af14
- effective_config · train_items.jsonl sha256 ad0daffd4336
- metrics · pilot.json sha256 18ddff092873
- predictions · pilot_predictions_base200.jsonl sha256 c69290c063d1
- predictions · pilot_predictions_treat200.jsonl sha256 46f0de2441c8
- predictions · predictions_base_untuned.jsonl sha256 235c3f808b95
- predictions · predictions_lora_sft_grader.jsonl sha256 ca19cceceed0
- metrics · scored-observations.jsonl sha256 2adc3b5c19b0
- metrics · decision-assessment.json sha256 55b80484732a
- metrics · base_summary.json sha256 0c5bfac2f98f
- metrics · treat_summary.json sha256 b2fc45c2183c
- metrics · train_history.json sha256 2c7b8aa936de
- metrics · checkpoints.json sha256 7a48f58ceaa9
- metrics · attempt1_base_summary.json sha256 dd9f0b6547f5
- metrics · attempt1_data_stats.json sha256 4195c2e107cd
- effective_config · attempt1_evaluator.json sha256 1fbe97792b07
- predictions · attempt1_predictions_base_untuned.jsonl sha256 6a9f4da5959d
- metrics · full_attempt1.log sha256 092884c02d36
- metrics · full_attempt2.log sha256 dd200ccbad5a
- metrics · treat.log sha256 c76d22b07751
- metrics · pilot2.log sha256 5bc4cd8a0b07
- Nov 3, 22:25 UTC · succeeded · done: base_untuned, lora_sft_grader · Rank-32 LoRA SFT of Qwen/Qwen3.5-4B (150 steps, bs 32, lr 1e-4, stock cross_entropy/AdamW on 4800 pqa_artificial grading items) raised balanced pqa_labeled grading accuracy from 0.7185 (untuned) to 0…
- Nov 3, 21:56 UTC · running · done: base_untuned · Pilot passed all activation gates; untuned Qwen/Qwen3.5-4B scored 0.7185 on the 2000 balanced pqa_labeled grading items under the final frozen evaluator 25131a53... (0.7205 in attempt 1 under evaluat…
- Nov 3, 21:51 UTC · running · done: base_untuned · Pilot passed all activation gates. Full attempt 1 completed 150 LoRA steps but crashed (script bug: extra forward on a nonexistent batch 150) before saving weights, so the treatment arm is being retr…
- Nov 3, 21:38 UTC · running · done: base_untuned · Pilot passed all activation gates; untuned Qwen/Qwen3.5-4B scored 0.7205 grading accuracy on the 2000 balanced pqa_labeled items, and the 150-step LoRA SFT treatment is training.
- Nov 3, 21:30 UTC · running · Pilot on shared Spindle (Qwen/Qwen3.5-4B, LoRA r32, 20 steps x 32) passed every activation gate check; full 150-step treatment training and 2000-item evals of both arms are running.
- Nov 3, 21:17 UTC · running · Data built (4800 train / 2000 eval grading items, balanced, PMID-disjoint); Qwen/Qwen3.5-4B is served on shared Spindle; activation/timing pilot running.
Artifacts
- correctness_preflight
- {'required': False, 'paths': []}
- correctness_validation
- {'status': 'not_applicable', 'required': False, 'checks': [], 'reason': 'experiment_features: custom_loss, custom_optimizer is false', 'evidence_source': 'executor report; remote execution is not attested', 'applicability': 'not_applicable', 'reported_verdict': 'supported'}
- decision
- {'version': 1, 'observations_file': {'name': 'scored-observations.jsonl', 'sha256': '2adc3b5c19b031c9c4eedabab8a703f522d10d9c27284d550430685e9a144220'}}
- decision_validation
- {'status': 'unverified', 'issues': ['Observation file name/hash is not retained for this run.'], 'criteria': [], 'outcome_reason': 'insufficient_evidence', 'applicability': {'check': 'decision_rule', 'status': 'required', 'enforce': True, 'reasons': ['experiment_features: paired_comparison is true'], 'features': {'paired_comparison': True, 'adaptive_selection': False}}, 'reported_verdict': 'supported'}
- evaluation
- {'version': 1, 'evaluators': {'25131a53fcdc110273727c96f2ec27d2ee549f02068efac718bed9e09fc9cbae': {'code_sha256': 'b1fed5101db396040622ed2181e2752107f1465f8649620caec32dce257e9b97', 'prompt_template': {'user': 'Context: {context}\nQuestion: {question}\nCandidate answer: {candidate}\nIs the candidate answer correct? Reply CORRECT or INCORRECT.', 'renderer': "tinker_cookbook renderers.get_renderer('qwen3', get_tokenizer('Qwen/Qwen3.5-4B')).build_generation_prompt([user]) (no system prompt; ends '<|im_start|>assistant\\n')", 'completions': {'CORRECT': [50564, 43347], 'INCORRECT': [37163, 842, 43347]}, 'deps': {'tinker': '0.37.0', 'tinker-cookbook': '0.5.9', 'datasets': '5.1.0', 'transformers': '5.22.1', 'torch': '2.15.0'}, 'max_seq_len': 1024}, 'decoding': {'method': 'forced-completion summed logprob via SamplingClient.compute_logprobs', 'temperature': 0, 'max_tokens': 0, 'stop': []}, 'parser': "prediction = 'CORRECT' if sum(logprobs[CORRECT tokens]) > sum(logprobs[INCORRECT tokens]) else 'INCORRECT'; value = int(prediction == gold label)", 'items': {'ids': ['pqa_labeled:21645374:CORRECT', 'pqa_labeled:21645374:INCORRECT', 'pqa_labeled:16418930:CORRECT', 'pqa_labeled:16418930:INCORRECT', 'pqa_labeled:9488747:CORRECT', 'pqa_labeled:9488747:INCORRECT', 'pqa_labeled:17208539:CORRECT', 'pqa_labeled:17208539:INCORRECT', 'pqa_labeled:10808977:CORRECT', 'pqa_labeled:10808977:INCORRECT', 'pqa_labeled:23831910:CORRECT', 'pqa_labeled:23831910:INCORRECT', 'pqa_labeled:26037986:CORRECT', 'pqa_labeled:26037986:INCORRECT', 'pqa_labeled:26852225:CORRECT', 'pqa_labeled:26852225:INCORRECT', 'pqa_labeled:17113061:CORRECT', 'pqa_labeled:17113061:INCORRECT', 'pqa_labeled:10966337:CORRECT', 'pqa_labeled:10966337:INCORRECT', 'pqa_labeled:25432938:CORRECT', 'pqa_labeled:25432938:INCORRECT', 'pqa_labeled:18847643:CORRECT', 'pqa_labeled:18847643:INCORRECT', 'pqa_labeled:18239988:CORRECT', 'pqa_labeled:18239988:INCORRECT', 'pqa_labeled:25957366:CORRECT', 'pqa_labeled:25957366:INCORRECT', 'pqa_labeled:24866606:CORRECT', 'pqa_labeled:24866606:INCORRECT', 'pqa_labeled:26578404:CORRECT', 'pqa_labeled:26578404:INCORRECT', 'pqa_labeled:11729377:CORRECT', 'pqa_labeled:11729377:INCORRECT', 'pqa_labeled:17096624:CORRECT', 'pqa_labeled:17096624:INCORRECT', 'pqa_labeled:22694248:CORRECT', 'pqa_labeled:22694248:INCORRECT', 'pqa_labeled:22990761:CORRECT', 'pqa_labeled:22990761:INCORRECT', 'pqa_labeled:19394934:CORRECT', 'pqa_labeled:19394934:INCORRECT', 'pqa_labeled:11481599:CORRECT', 'pqa_labeled:11481599:INCORRECT', 'pqa_labeled:21669959:CORRECT', 'pqa_labeled:21669959:INCORRECT', 'pqa_labeled:23806388:CORRECT', 'pqa_labeled:23806388:INCORRECT', 'pqa_labeled:17919952:CORRECT', 'pqa_labeled:17919952:INCORRECT', 'pqa_labeled:10966943:CORRECT', 'pqa_labeled:10966943:INCORRECT', 'pqa_labeled:23690198:CORRECT', 'pqa_labeled:23690198:INCORRECT', 'pqa_labeled:17940352:CORRECT', 'pqa_labeled:17940352:INCORRECT', 'pqa_labeled:20537205:CORRECT', 'pqa_labeled:20537205:INCORRECT', 'pqa_labeled:28707539:CORRECT', 'pqa_labeled:28707539:INCORRECT', 'pqa_labeled:7482275:CORRECT', 'pqa_labeled:7482275:INCORRECT', 'pqa_labeled:24183388:CORRECT', 'pqa_labeled:24183388:INCORRECT', 'pqa_labeled:9645785:CORRECT', 'pqa_labeled:9645785:INCORRECT', 'pqa_labeled:26298839:CORRECT', 'pqa_labeled:26298839:INCORRECT', 'pqa_labeled:24153338:CORRECT', 'pqa_labeled:24153338:INCORRECT', 'pqa_labeled:18534072:CORRECT', 'pqa_labeled:18534072:INCORRECT', 'pqa_labeled:8847047:CORRECT', 'pqa_labeled:8847047:INCORRECT', 'pqa_labeled:10575390:CORRECT', 'pqa_labeled:10575390:INCORRECT', 'pqa_labeled:20084845:CORRECT', 'pqa_labeled:20084845:INCORRECT', 'pqa_labeled:15703931:CORRECT', 'pqa_labeled:15703931:INCORRECT', 'pqa_labeled:18269157:CORRECT', 'pqa_labeled:18269157:INCORRECT', 'pqa_labeled:25489696:CORRECT', 'pqa_labeled:25489696:INCORRECT', 'pqa_labeled:14599616:CORRECT', 'pqa_labeled:14599616:INCORRECT', 'pqa_labeled:22537902:CORRECT', 'pqa_labeled:22537902:INCORRECT', 'pqa_labeled:19054501:CORRECT', 'pqa_labeled:19054501:INCORRECT', 'pqa_labeled:16432652:CORRECT', 'pqa_labeled:16432652:INCORRECT', 'pqa_labeled:19504993:CORRECT', 'pqa_labeled:19504993:INCORRECT', 'pqa_labeled:20571467:CORRECT', 'pqa_labeled:20571467:INCORRECT', 'pqa_labeled:24237112:CORRECT', 'pqa_labeled:24237112:INCORRECT', 'pqa_labeled:21402341:CORRECT', 'pqa_labeled:21402341:INCORRECT', 'pqa_labeled:20082356:CORRECT', 'pqa_labeled:20082356:INCORRECT', 'pqa_labeled:26606599:CORRECT', 'pqa_labeled:26606599:INCORRECT', 'pqa_labeled:11340218:CORRECT', 'pqa_labeled:11340218:INCORRECT', 'pqa_labeled:25481573:CORRECT', 'pqa_labeled:25481573:INCORRECT', 'pqa_labeled:25277731:CORRECT', 'pqa_labeled:25277731:INCORRECT', 'pqa_labeled:25475395:CORRECT', 'pqa_labeled:25475395:INCORRECT', 'pqa_labeled:23177368:CORRECT', 'pqa_labeled:23177368:INCORRECT', 'pqa_labeled:17179167:CORRECT', 'pqa_labeled:17179167:INCORRECT', 'pqa_labeled:14612308:CORRECT', 'pqa_labeled:14612308:INCORRECT', 'pqa_labeled:27491658:CORRECT', 'pqa_labeled:27491658:INCORRECT', 'pqa_labeled:19822586:CORRECT', 'pqa_labeled:19822586:INCORRECT', 'pqa_labeled:27643961:CORRECT', 'pqa_labeled:27643961:INCORRECT', 'pqa_labeled:23539689:CORRECT', 'pqa_labeled:23539689:INCORRECT', 'pqa_labeled:22453060:CORRECT', 'pqa_labeled:22453060:INCORRECT', 'pqa_labeled:22227642:CORRECT', 'pqa_labeled:22227642:INCORRECT', 'pqa_labeled:12380309:CORRECT', 'pqa_labeled:12380309:INCORRECT', 'pqa_labeled:22186742:CORRECT', 'pqa_labeled:22186742:INCORRECT', 'pqa_labeled:22188074:CORRECT', 'pqa_labeled:22188074:INCORRECT', 'pqa_labeled:27989969:CORRECT', 'pqa_labeled:27989969:INCORRECT', 'pqa_labeled:18607272:CORRECT', 'pqa_labeled:18607272:INCORRECT', 'pqa_labeled:18235194:CORRECT', 'pqa_labeled:18235194:INCORRECT', 'pqa_labeled:18049437:CORRECT', 'pqa_labeled:18049437:INCORRECT', 'pqa_labeled:15597845:CORRECT', 'pqa_labeled:15597845:INCORRECT', 'pqa_labeled:24996865:CORRECT', 'pqa_labeled:24996865:INCORRECT', 'pqa_labeled:23361217:CORRECT', 'pqa_labeled:23361217:INCORRECT', 'pqa_labeled:17489316:CORRECT', 'pqa_labeled:17489316:INCORRECT', 'pqa_labeled:14518645:CORRECT', 'pqa_labeled:14518645:INCORRECT', 'pqa_labeled:20337202:CORRECT', 'pqa_labeled:20337202:INCORRECT', 'pqa_labeled:26449554:CORRECT', 'pqa_labeled:26449554:INCORRECT', 'pqa_labeled:26215326:CORRECT', 'pqa_labeled:26215326:INCORRECT', 'pqa_labeled:29112560:CORRECT', 'pqa_labeled:29112560:INCORRECT', 'pqa_labeled:24315783:CORRECT', 'pqa_labeled:24315783:INCORRECT', 'pqa_labeled:9381529:CORRECT', 'pqa_labeled:9381529:INCORRECT', 'pqa_labeled:8985020:CORRECT', 'pqa_labeled:8985020:INCORRECT', 'pqa_labeled:26708803:CORRECT', 'pqa_labeled:26708803:INCORRECT', 'pqa_labeled:22427593:CORRECT', 'pqa_labeled:22427593:INCORRECT', 'pqa_labeled:11570976:CORRECT', 'pqa_labeled:11570976:INCORRECT', 'pqa_labeled:19757704:CORRECT', 'pqa_labeled:19757704:INCORRECT', 'pqa_labeled:27592038:CORRECT', 'pqa_labeled:27592038:INCORRECT', 'pqa_labeled:27044366:CORRECT', 'pqa_labeled:27044366:INCORRECT', 'pqa_labeled:9792366:CORRECT', 'pqa_labeled:9792366:INCORRECT', 'pqa_labeled:17562682:CORRECT', 'pqa_labeled:17562682:INCORRECT', 'pqa_labeled:15800018:CORRECT', 'pqa_labeled:15800018:INCORRECT', 'pqa_labeled:14978612:CORRECT', 'pqa_labeled:14978612:INCORRECT', 'pqa_labeled:18843057:CORRECT', 'pqa_labeled:18843057:INCORRECT', 'pqa_labeled:23076787:CORRECT', 'pqa_labeled:23076787:INCORRECT', 'pqa_labeled:9199905:CORRECT', 'pqa_labeled:9199905:INCORRECT', 'pqa_labeled:23999452:CORRECT', 'pqa_labeled:23999452:INCORRECT', 'pqa_labeled:22534881:CORRECT', 'pqa_labeled:22534881:INCORRECT', 'pqa_labeled:24785562:CORRECT', 'pqa_labeled:24785562:INCORRECT', 'pqa_labeled:22564465:CORRECT', 'pqa_labeled:22564465:INCORRECT', 'pqa_labeled:27456836:CORRECT', 'pqa_labeled:27456836:INCORRECT', 'pqa_labeled:27287237:CORRECT', 'pqa_labeled:27287237:INCORRECT', 'pqa_labeled:14697414:CORRECT', 'pqa_labeled:14697414:INCORRECT', 'pqa_labeled:26686513:CORRECT', 'pqa_labeled:26686513:INCORRECT', 'pqa_labeled:15530261:CORRECT', 'pqa_labeled:15530261:INCORRECT', 'pqa_labeled:24160268:CORRECT', 'pqa_labeled:24160268:INCORRECT', 'pqa_labeled:21823940:CORRECT', 'pqa_labeled:21823940:INCORRECT', 'pqa_labeled:27217036:CORRECT', 'pqa_labeled:27217036:INCORRECT', 'pqa_labeled:18565233:CORRECT', 'pqa_labeled:18565233:INCORRECT', 'pqa_labeled:19694846:CORRECT', 'pqa_labeled:19694846:INCORRECT', 'pqa_labeled:27184293:CORRECT', 'pqa_labeled:27184293:INCORRECT', 'pqa_labeled:19459018:CORRECT', 'pqa_labeled:19459018:INCORRECT', 'pqa_labeled:22042121:CORRECT', 'pqa_labeled:22042121:INCORRECT', 'pqa_labeled:16100194:CORRECT', 'pqa_labeled:16100194:INCORRECT', 'pqa_labeled:25480629:CORRECT', 'pqa_labeled:25480629:INCORRECT', 'pqa_labeled:17453263:CORRECT', 'pqa_labeled:17453263:INCORRECT', 'pqa_labeled:18322741:CORRECT', 'pqa_labeled:18322741:INCORRECT', 'pqa_labeled:19106867:CORRECT', 'pqa_labeled:19106867:INCORRECT', 'pqa_labeled:25691513:CORRECT', 'pqa_labeled:25691513:INCORRECT', 'pqa_labeled:11035130:CORRECT', 'pqa_labeled:11035130:INCORRECT', 'pqa_labeled:19409117:CORRECT', 'pqa_labeled:19409117:INCORRECT', 'pqa_labeled:21900017:CORRECT', 'pqa_labeled:21900017:INCORRECT', 'pqa_labeled:16968876:CORRECT', 'pqa_labeled:16968876:INCORRECT', 'pqa_labeled:18540901:CORRECT', 'pqa_labeled:18540901:INCORRECT', 'pqa_labeled:27448572:CORRECT', 'pqa_labeled:27448572:INCORRECT', 'pqa_labeled:17621202:CORRECT', 'pqa_labeled:17621202:INCORRECT', 'pqa_labeled:25987398:CORRECT', 'pqa_labeled:25987398:INCORRECT', 'pqa_labeled:16816043:CORRECT', 'pqa_labeled:16816043:INCORRECT', 'pqa_labeled:12920330:CORRECT', 'pqa_labeled:12920330:INCORRECT', 'pqa_labeled:23497210:CORRECT', 'pqa_labeled:23497210:INCORRECT', 'pqa_labeled:21952349:CORRECT', 'pqa_labeled:21952349:INCORRECT', 'pqa_labeled:21712147:CORRECT', 'pqa_labeled:21712147:INCORRECT', 'pqa_labeled:25311479:CORRECT', 'pqa_labeled:25311479:INCORRECT', 'pqa_labeled:20602784:CORRECT', 'pqa_labeled:20602784:INCORRECT', 'pqa_labeled:12836106:CORRECT', 'pqa_labeled:12836106:INCORRECT', 'pqa_labeled:25588461:CORRECT', 'pqa_labeled:25588461:INCORRECT', 'pqa_labeled:19299238:CORRECT', 'pqa_labeled:19299238:INCORRECT', 'pqa_labeled:22706226:CORRECT', 'pqa_labeled:22706226:INCORRECT', 'pqa_labeled:12913878:CORRECT', 'pqa_labeled:12913878:INCORRECT', 'pqa_labeled:16769333:CORRECT', 'pqa_labeled:16769333:INCORRECT', 'pqa_labeled:22497340:CORRECT', 'pqa_labeled:22497340:INCORRECT', 'pqa_labeled:10223070:CORRECT', 'pqa_labeled:10223070:INCORRECT', 'pqa_labeled:8566975:CORRECT', 'pqa_labeled:8566975:INCORRECT', 'pqa_labeled:25186850:CORRECT', 'pqa_labeled:25186850:INCORRECT', 'pqa_labeled:9427037:CORRECT', 'pqa_labeled:9427037:INCORRECT', 'pqa_labeled:28359277:CORRECT', 'pqa_labeled:28359277:INCORRECT', 'pqa_labeled:11411430:CORRECT', 'pqa_labeled:11411430:INCORRECT', 'pqa_labeled:16956164:CORRECT', 'pqa_labeled:16956164:INCORRECT', 'pqa_labeled:15687156:CORRECT', 'pqa_labeled:15687156:INCORRECT', 'pqa_labeled:28127977:CORRECT', 'pqa_labeled:28127977:INCORRECT', 'pqa_labeled:16809243:CORRECT', 'pqa_labeled:16809243:INCORRECT', 'pqa_labeled:17276182:CORRECT', 'pqa_labeled:17276182:INCORRECT', 'pqa_labeled:21123461:CORRECT', 'pqa_labeled:21123461:INCORRECT', 'pqa_labeled:22428608:CORRECT', 'pqa_labeled:22428608:INCORRECT', 'pqa_labeled:27858166:CORRECT', 'pqa_labeled:27858166:INCORRECT', 'pqa_labeled:23791827:CORRECT', 'pqa_labeled:23791827:INCORRECT', 'pqa_labeled:18243752:CORRECT', 'pqa_labeled:18243752:INCORRECT', 'pqa_labeled:17279467:CORRECT', 'pqa_labeled:17279467:INCORRECT', 'pqa_labeled:22758782:CORRECT', 'pqa_labeled:22758782:INCORRECT', 'pqa_labeled:15223725:CORRECT', 'pqa_labeled:15223725:INCORRECT', 'pqa_labeled:19482903:CORRECT', 'pqa_labeled:19482903:INCORRECT', 'pqa_labeled:25752912:CORRECT', 'pqa_labeled:25752912:INCORRECT', 'pqa_labeled:21946341:CORRECT', 'pqa_labeled:21946341:INCORRECT', 'pqa_labeled:16428354:CORRECT', 'pqa_labeled:16428354:INCORRECT', 'pqa_labeled:19302863:CORRECT', 'pqa_labeled:19302863:INCORRECT', 'pqa_labeled:24245816:CORRECT', 'pqa_labeled:24245816:INCORRECT', 'pqa_labeled:24666444:CORRECT', 'pqa_labeled:24666444:INCORRECT', 'pqa_labeled:19913785:CORRECT', 'pqa_labeled:19913785:INCORRECT', 'pqa_labeled:1571683:CORRECT', 'pqa_labeled:1571683:INCORRECT', 'pqa_labeled:15631914:CORRECT', 'pqa_labeled:15631914:INCORRECT', 'pqa_labeled:11970923:CORRECT', 'pqa_labeled:11970923:INCORRECT', 'pqa_labeled:20121683:CORRECT', 'pqa_labeled:20121683:INCORRECT', 'pqa_labeled:27281318:CORRECT', 'pqa_labeled:27281318:INCORRECT', 'pqa_labeled:12846929:CORRECT', 'pqa_labeled:12846929:INCORRECT', 'pqa_labeled:26505821:CORRECT', 'pqa_labeled:26505821:INCORRECT', 'pqa_labeled:25156467:CORRECT', 'pqa_labeled:25156467:INCORRECT', 'pqa_labeled:22023714:CORRECT', 'pqa_labeled:22023714:INCORRECT', 'pqa_labeled:16046584:CORRECT', 'pqa_labeled:16046584:INCORRECT', 'pqa_labeled:16155169:CORRECT', 'pqa_labeled:16155169:INCORRECT', 'pqa_labeled:19398929:CORRECT', 'pqa_labeled:19398929:INCORRECT', 'pqa_labeled:28143468:CORRECT', 'pqa_labeled:28143468:INCORRECT', 'pqa_labeled:9483814:CORRECT', 'pqa_labeled:9483814:INCORRECT', 'pqa_labeled:22720085:CORRECT', 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'pqa_labeled:11483547:INCORRECT', 'pqa_labeled:27884344:CORRECT', 'pqa_labeled:27884344:INCORRECT', 'pqa_labeled:18800356:CORRECT', 'pqa_labeled:18800356:INCORRECT', 'pqa_labeled:22301406:CORRECT', 'pqa_labeled:22301406:INCORRECT', 'pqa_labeled:26079501:CORRECT', 'pqa_labeled:26079501:INCORRECT', 'pqa_labeled:15774570:CORRECT', 'pqa_labeled:15774570:INCORRECT', 'pqa_labeled:18319270:CORRECT', 'pqa_labeled:18319270:INCORRECT', 'pqa_labeled:26209118:CORRECT', 'pqa_labeled:26209118:INCORRECT', 'pqa_labeled:11713724:CORRECT', 'pqa_labeled:11713724:INCORRECT', 'pqa_labeled:25070942:CORRECT', 'pqa_labeled:25070942:INCORRECT', 'pqa_labeled:19683101:CORRECT', 'pqa_labeled:19683101:INCORRECT', 'pqa_labeled:10783841:CORRECT', 'pqa_labeled:10783841:INCORRECT', 'pqa_labeled:11862129:CORRECT', 'pqa_labeled:11862129:INCORRECT', 'pqa_labeled:23455575:CORRECT', 'pqa_labeled:23455575:INCORRECT', 'pqa_labeled:21848798:CORRECT', 'pqa_labeled:21848798:INCORRECT', 'pqa_labeled:25103647:CORRECT', 'pqa_labeled:25103647:INCORRECT', 'pqa_labeled:19406119:CORRECT', 'pqa_labeled:19406119:INCORRECT', 'pqa_labeled:24359102:CORRECT', 'pqa_labeled:24359102:INCORRECT', 'pqa_labeled:18802997:CORRECT', 'pqa_labeled:18802997:INCORRECT', 'pqa_labeled:26304701:CORRECT', 'pqa_labeled:26304701:INCORRECT', 'pqa_labeled:19058191:CORRECT', 'pqa_labeled:19058191:INCORRECT', 'pqa_labeled:27549226:CORRECT', 'pqa_labeled:27549226:INCORRECT', 'pqa_labeled:24799031:CORRECT', 'pqa_labeled:24799031:INCORRECT', 'pqa_labeled:25043083:CORRECT', 'pqa_labeled:25043083:INCORRECT', 'pqa_labeled:26516021:CORRECT', 'pqa_labeled:26516021:INCORRECT', 'pqa_labeled:23736032:CORRECT', 'pqa_labeled:23736032:INCORRECT', 'pqa_labeled:17312514:CORRECT', 'pqa_labeled:17312514:INCORRECT', 'pqa_labeled:23002947:CORRECT', 'pqa_labeled:23002947:INCORRECT', 'pqa_labeled:23453079:CORRECT', 'pqa_labeled:23453079:INCORRECT', 'pqa_labeled:15053041:CORRECT', 'pqa_labeled:15053041:INCORRECT', 'pqa_labeled:9465206:CORRECT', 'pqa_labeled:9465206:INCORRECT', 'pqa_labeled:19593710:CORRECT', 'pqa_labeled:19593710:INCORRECT', 'pqa_labeled:8521557:CORRECT', 'pqa_labeled:8521557:INCORRECT', 'pqa_labeled:24340838:CORRECT', 'pqa_labeled:24340838:INCORRECT', 'pqa_labeled:24751724:CORRECT', 'pqa_labeled:24751724:INCORRECT', 'pqa_labeled:21368683:CORRECT', 'pqa_labeled:21368683:INCORRECT', 'pqa_labeled:27832831:CORRECT', 'pqa_labeled:27832831:INCORRECT', 'pqa_labeled:15208005:CORRECT', 'pqa_labeled:15208005:INCORRECT', 'pqa_labeled:24958650:CORRECT', 'pqa_labeled:24958650:INCORRECT', 'pqa_labeled:16713745:CORRECT', 'pqa_labeled:16713745:INCORRECT', 'pqa_labeled:24669960:CORRECT', 'pqa_labeled:24669960:INCORRECT', 'pqa_labeled:9278754:CORRECT', 'pqa_labeled:9278754:INCORRECT', 'pqa_labeled:8738894:CORRECT', 'pqa_labeled:8738894:INCORRECT', 'pqa_labeled:24671913:CORRECT', 'pqa_labeled:24671913:INCORRECT', 'pqa_labeled:22540518:CORRECT', 'pqa_labeled:22540518:INCORRECT', 'pqa_labeled:16538201:CORRECT', 'pqa_labeled:16538201:INCORRECT', 'pqa_labeled:17054994:CORRECT', 'pqa_labeled:17054994:INCORRECT', 'pqa_labeled:26999038:CORRECT', 'pqa_labeled:26999038:INCORRECT', 'pqa_labeled:23598835:CORRECT', 'pqa_labeled:23598835:INCORRECT', 'pqa_labeled:17890090:CORRECT', 'pqa_labeled:17890090:INCORRECT', 'pqa_labeled:22813804:CORRECT', 'pqa_labeled:22813804:INCORRECT', 'pqa_labeled:26923375:CORRECT', 'pqa_labeled:26923375:INCORRECT', 'pqa_labeled:20304513:CORRECT', 'pqa_labeled:20304513:INCORRECT', 'pqa_labeled:21689015:CORRECT', 'pqa_labeled:21689015:INCORRECT', 'pqa_labeled:10811329:CORRECT', 'pqa_labeled:10811329:INCORRECT', 'pqa_labeled:10834864:CORRECT', 'pqa_labeled:10834864:INCORRECT', 'pqa_labeled:27909738:CORRECT', 'pqa_labeled:27909738:INCORRECT', 'pqa_labeled:26063028:CORRECT', 'pqa_labeled:26063028:INCORRECT', 'pqa_labeled:25034219:CORRECT', 'pqa_labeled:25034219:INCORRECT', 'pqa_labeled:25521278:CORRECT', 'pqa_labeled:25521278:INCORRECT', 'pqa_labeled:27908583:CORRECT', 'pqa_labeled:27908583:INCORRECT', 'pqa_labeled:23422012:CORRECT', 'pqa_labeled:23422012:INCORRECT', 'pqa_labeled:11500608:CORRECT', 'pqa_labeled:11500608:INCORRECT', 'pqa_labeled:8111516:CORRECT', 'pqa_labeled:8111516:INCORRECT', 'pqa_labeled:25604390:CORRECT', 'pqa_labeled:25604390:INCORRECT', 'pqa_labeled:25985014:CORRECT', 'pqa_labeled:25985014:INCORRECT', 'pqa_labeled:14627582:CORRECT', 'pqa_labeled:14627582:INCORRECT', 'pqa_labeled:18570208:CORRECT', 'pqa_labeled:18570208:INCORRECT', 'pqa_labeled:23448747:CORRECT', 'pqa_labeled:23448747:INCORRECT', 'pqa_labeled:20156655:CORRECT', 'pqa_labeled:20156655:INCORRECT', 'pqa_labeled:16147837:CORRECT', 'pqa_labeled:16147837:INCORRECT', 'pqa_labeled:16249670:CORRECT', 'pqa_labeled:16249670:INCORRECT', 'pqa_labeled:24495711:CORRECT', 'pqa_labeled:24495711:INCORRECT', 'pqa_labeled:20101129:CORRECT', 'pqa_labeled:20101129:INCORRECT', 'pqa_labeled:17593459:CORRECT', 'pqa_labeled:17593459:INCORRECT', 'pqa_labeled:24577079:CORRECT', 'pqa_labeled:24577079:INCORRECT', 'pqa_labeled:9582182:CORRECT', 'pqa_labeled:9582182:INCORRECT', 'pqa_labeled:17715311:CORRECT', 'pqa_labeled:17715311:INCORRECT', 'pqa_labeled:12094116:CORRECT', 'pqa_labeled:12094116:INCORRECT', 'pqa_labeled:19430778:CORRECT', 'pqa_labeled:19430778:INCORRECT', 'pqa_labeled:12848629:CORRECT', 'pqa_labeled:12848629:INCORRECT', 'pqa_labeled:10732884:CORRECT', 'pqa_labeled:10732884:INCORRECT', 'pqa_labeled:23568387:CORRECT', 'pqa_labeled:23568387:INCORRECT', 'pqa_labeled:25675614:CORRECT', 'pqa_labeled:25675614:INCORRECT', 'pqa_labeled:26864326:CORRECT', 'pqa_labeled:26864326:INCORRECT', 'pqa_labeled:26784147:CORRECT', 'pqa_labeled:26784147:INCORRECT', 'pqa_labeled:20850631:CORRECT', 'pqa_labeled:20850631:INCORRECT', 'pqa_labeled:22849512:CORRECT', 'pqa_labeled:22849512:INCORRECT', 'pqa_labeled:27642458:CORRECT', 'pqa_labeled:27642458:INCORRECT', 'pqa_labeled:17403428:CORRECT', 'pqa_labeled:17403428:INCORRECT', 'pqa_labeled:21252642:CORRECT', 'pqa_labeled:21252642:INCORRECT', 'pqa_labeled:25503376:CORRECT', 'pqa_labeled:25503376:INCORRECT', 'pqa_labeled:12172698:CORRECT', 'pqa_labeled:12172698:INCORRECT', 'pqa_labeled:19351635:CORRECT', 'pqa_labeled:19351635:INCORRECT', 'pqa_labeled:17551944:CORRECT', 'pqa_labeled:17551944:INCORRECT', 'pqa_labeled:17606778:CORRECT', 'pqa_labeled:17606778:INCORRECT', 'pqa_labeled:24318956:CORRECT', 'pqa_labeled:24318956:INCORRECT', 'pqa_labeled:26044262:CORRECT', 'pqa_labeled:26044262:INCORRECT', 'pqa_labeled:20011163:CORRECT', 'pqa_labeled:20011163:INCORRECT', 'pqa_labeled:16735905:CORRECT', 'pqa_labeled:16735905:INCORRECT', 'pqa_labeled:18670651:CORRECT', 'pqa_labeled:18670651:INCORRECT', 'pqa_labeled:11034241:CORRECT', 'pqa_labeled:11034241:INCORRECT', 'pqa_labeled:24013712:CORRECT', 'pqa_labeled:24013712:INCORRECT', 'pqa_labeled:23240452:CORRECT', 'pqa_labeled:23240452:INCORRECT', 'pqa_labeled:21420186:CORRECT', 'pqa_labeled:21420186:INCORRECT', 'pqa_labeled:22302761:CORRECT', 'pqa_labeled:22302761:INCORRECT', 'pqa_labeled:21979183:CORRECT', 'pqa_labeled:21979183:INCORRECT', 'pqa_labeled:12607120:CORRECT', 'pqa_labeled:12607120:INCORRECT', 'pqa_labeled:21914194:CORRECT', 'pqa_labeled:21914194:INCORRECT', 'pqa_labeled:25725704:CORRECT', 'pqa_labeled:25725704:INCORRECT', 'pqa_labeled:24516646:CORRECT', 'pqa_labeled:24516646:INCORRECT', 'pqa_labeled:28247485:CORRECT', 'pqa_labeled:28247485:INCORRECT', 'pqa_labeled:11334578:CORRECT', 'pqa_labeled:11334578:INCORRECT', 'pqa_labeled:21593045:CORRECT', 'pqa_labeled:21593045:INCORRECT', 'pqa_labeled:22902073:CORRECT', 'pqa_labeled:22902073:INCORRECT', 'pqa_labeled:26471488:CORRECT', 'pqa_labeled:26471488:INCORRECT', 'pqa_labeled:16647887:CORRECT', 'pqa_labeled:16647887:INCORRECT', 'pqa_labeled:22668712:CORRECT', 'pqa_labeled:22668712:INCORRECT', 'pqa_labeled:18439500:CORRECT', 'pqa_labeled:18439500:INCORRECT', 'pqa_labeled:23347337:CORRECT', 'pqa_labeled:23347337:INCORRECT', 'pqa_labeled:22970993:CORRECT', 'pqa_labeled:22970993:INCORRECT', 'pqa_labeled:16498158:CORRECT', 'pqa_labeled:16498158:INCORRECT', 'pqa_labeled:24622801:CORRECT', 'pqa_labeled:24622801:INCORRECT', 'pqa_labeled:15000338:CORRECT', 'pqa_labeled:15000338:INCORRECT', 'pqa_labeled:22491528:CORRECT', 'pqa_labeled:22491528:INCORRECT', 'pqa_labeled:11247896:CORRECT', 'pqa_labeled:11247896:INCORRECT', 'pqa_labeled:19145527:CORRECT', 'pqa_labeled:19145527:INCORRECT', 'pqa_labeled:18568239:CORRECT', 'pqa_labeled:18568239:INCORRECT', 'pqa_labeled:22075911:CORRECT', 'pqa_labeled:22075911:INCORRECT', 'pqa_labeled:10401824:CORRECT', 'pqa_labeled:10401824:INCORRECT', 'pqa_labeled:21880023:CORRECT', 'pqa_labeled:21880023:INCORRECT', 'pqa_labeled:21726930:CORRECT', 'pqa_labeled:21726930:INCORRECT', 'pqa_labeled:22768311:CORRECT', 'pqa_labeled:22768311:INCORRECT', 'pqa_labeled:25636371:CORRECT', 'pqa_labeled:25636371:INCORRECT', 'pqa_labeled:15050326:CORRECT', 'pqa_labeled:15050326:INCORRECT', 'pqa_labeled:23412195:CORRECT', 'pqa_labeled:23412195:INCORRECT', 'pqa_labeled:16968183:CORRECT', 'pqa_labeled:16968183:INCORRECT', 'pqa_labeled:23359100:CORRECT', 'pqa_labeled:23359100:INCORRECT', 'pqa_labeled:15943725:CORRECT', 'pqa_labeled:15943725:INCORRECT', 'pqa_labeled:25735444:CORRECT', 'pqa_labeled:25735444:INCORRECT', 'pqa_labeled:9722752:CORRECT', 'pqa_labeled:9722752:INCORRECT', 'pqa_labeled:23870157:CORRECT', 'pqa_labeled:23870157:INCORRECT', 'pqa_labeled:22303473:CORRECT', 'pqa_labeled:22303473:INCORRECT', 'pqa_labeled:24995509:CORRECT', 'pqa_labeled:24995509:INCORRECT', 'pqa_labeled:24270957:CORRECT', 'pqa_labeled:24270957:INCORRECT', 'pqa_labeled:23848044:CORRECT', 'pqa_labeled:23848044:INCORRECT', 'pqa_labeled:9920954:CORRECT', 'pqa_labeled:9920954:INCORRECT', 'pqa_labeled:21276532:CORRECT', 'pqa_labeled:21276532:INCORRECT', 'pqa_labeled:23379759:CORRECT', 'pqa_labeled:23379759:INCORRECT', 'pqa_labeled:25891436:CORRECT', 'pqa_labeled:25891436:INCORRECT', 'pqa_labeled:24450673:CORRECT', 'pqa_labeled:24450673:INCORRECT', 'pqa_labeled:17914515:CORRECT', 'pqa_labeled:17914515:INCORRECT', 'pqa_labeled:24739448:CORRECT', 'pqa_labeled:24739448:INCORRECT', 'pqa_labeled:19444061:CORRECT', 'pqa_labeled:19444061:INCORRECT', 'pqa_labeled:25669733:CORRECT', 'pqa_labeled:25669733:INCORRECT', 'pqa_labeled:20577124:CORRECT', 'pqa_labeled:20577124:INCORRECT', 'pqa_labeled:21592383:CORRECT', 'pqa_labeled:21592383:INCORRECT', 'pqa_labeled:11053064:CORRECT', 'pqa_labeled:11053064:INCORRECT', 'pqa_labeled:9745063:CORRECT', 'pqa_labeled:9745063:INCORRECT', 'pqa_labeled:11138995:CORRECT', 'pqa_labeled:11138995:INCORRECT', 'pqa_labeled:15475728:CORRECT', 'pqa_labeled:15475728:INCORRECT', 'pqa_labeled:12121321:CORRECT', 'pqa_labeled:12121321:INCORRECT', 'pqa_labeled:17342562:CORRECT', 'pqa_labeled:17342562:INCORRECT', 'pqa_labeled:28011794:CORRECT', 'pqa_labeled:28011794:INCORRECT', 'pqa_labeled:24098953:CORRECT', 'pqa_labeled:24098953:INCORRECT', 'pqa_labeled:24827404:CORRECT', 'pqa_labeled:24827404:INCORRECT', 'pqa_labeled:28407529:CORRECT', 'pqa_labeled:28407529:INCORRECT', 'pqa_labeled:27928673:CORRECT', 'pqa_labeled:27928673:INCORRECT', 'pqa_labeled:22011946:CORRECT', 'pqa_labeled:22011946:INCORRECT', 'pqa_labeled:23517744:CORRECT', 'pqa_labeled:23517744:INCORRECT', 'pqa_labeled:20842006:CORRECT', 'pqa_labeled:20842006:INCORRECT', 'pqa_labeled:9140335:CORRECT', 'pqa_labeled:9140335:INCORRECT', 'pqa_labeled:12142826:CORRECT', 'pqa_labeled:12142826:INCORRECT', 'pqa_labeled:22382608:CORRECT', 'pqa_labeled:22382608:INCORRECT', 'pqa_labeled:17329379:CORRECT', 'pqa_labeled:17329379:INCORRECT', 'pqa_labeled:27288618:CORRECT', 'pqa_labeled:27288618:INCORRECT', 'pqa_labeled:21873082:CORRECT', 'pqa_labeled:21873082:INCORRECT', 'pqa_labeled:25810292:CORRECT', 'pqa_labeled:25810292:INCORRECT', 'pqa_labeled:21739621:CORRECT', 'pqa_labeled:21739621:INCORRECT', 'pqa_labeled:20073599:CORRECT', 'pqa_labeled:20073599:INCORRECT', 'pqa_labeled:21845457:CORRECT', 'pqa_labeled:21845457:INCORRECT', 'pqa_labeled:16216859:CORRECT', 'pqa_labeled:16216859:INCORRECT', 'pqa_labeled:19103915:CORRECT', 'pqa_labeled:19103915:INCORRECT', 'pqa_labeled:22521460:CORRECT', 'pqa_labeled:22521460:INCORRECT', 'pqa_labeled:17062234:CORRECT', 'pqa_labeled:17062234:INCORRECT', 'pqa_labeled:26126304:CORRECT', 'pqa_labeled:26126304:INCORRECT', 'pqa_labeled:19578820:CORRECT', 'pqa_labeled:19578820:INCORRECT', 'pqa_labeled:21228436:CORRECT', 'pqa_labeled:21228436:INCORRECT', 'pqa_labeled:23972333:CORRECT', 'pqa_labeled:23972333:INCORRECT', 'pqa_labeled:23719685:CORRECT', 'pqa_labeled:23719685:INCORRECT', 'pqa_labeled:11601252:CORRECT', 'pqa_labeled:11601252:INCORRECT', 'pqa_labeled:23506394:CORRECT', 'pqa_labeled:23506394:INCORRECT', 'pqa_labeled:19575307:CORRECT', 'pqa_labeled:19575307:INCORRECT', 'pqa_labeled:11977907:CORRECT', 'pqa_labeled:11977907:INCORRECT', 'pqa_labeled:12626177:CORRECT', 'pqa_labeled:12626177:INCORRECT', 'pqa_labeled:15483019:CORRECT', 'pqa_labeled:15483019:INCORRECT', 'pqa_labeled:18693227:CORRECT', 'pqa_labeled:18693227:INCORRECT', 'pqa_labeled:27131771:CORRECT', 'pqa_labeled:27131771:INCORRECT', 'pqa_labeled:24783217:CORRECT', 'pqa_labeled:24783217:INCORRECT', 'pqa_labeled:17916877:CORRECT', 'pqa_labeled:17916877:INCORRECT', 'pqa_labeled:8375607:CORRECT', 'pqa_labeled:8375607:INCORRECT', 'pqa_labeled:11955750:CORRECT', 'pqa_labeled:11955750:INCORRECT', 'pqa_labeled:27040842:CORRECT', 'pqa_labeled:27040842:INCORRECT', 'pqa_labeled:17244100:CORRECT', 'pqa_labeled:17244100:INCORRECT', 'pqa_labeled:15708048:CORRECT', 'pqa_labeled:15708048:INCORRECT', 'pqa_labeled:11438275:CORRECT', 'pqa_labeled:11438275:INCORRECT', 'pqa_labeled:22513023:CORRECT', 'pqa_labeled:22513023:INCORRECT', 'pqa_labeled:27146470:CORRECT', 'pqa_labeled:27146470:INCORRECT', 'pqa_labeled:8165771:CORRECT', 'pqa_labeled:8165771:INCORRECT', 'pqa_labeled:23677366:CORRECT', 'pqa_labeled:23677366:INCORRECT', 'pqa_labeled:19237087:CORRECT', 'pqa_labeled:19237087:INCORRECT', 'pqa_labeled:10456814:CORRECT', 'pqa_labeled:10456814:INCORRECT', 'pqa_labeled:8921484:CORRECT', 'pqa_labeled:8921484:INCORRECT', 'pqa_labeled:16564683:CORRECT', 'pqa_labeled:16564683:INCORRECT', 'pqa_labeled:23147106:CORRECT', 'pqa_labeled:23147106:INCORRECT', 'pqa_labeled:21550158:CORRECT', 'pqa_labeled:21550158:INCORRECT', 'pqa_labeled:17559449:CORRECT', 'pqa_labeled:17559449:INCORRECT']}}}, 'scores': [{'arm': 'baseline', 'metric': 'accuracy', 'value': 0.7185, 'evaluator_id': '25131a53fcdc110273727c96f2ec27d2ee549f02068efac718bed9e09fc9cbae', 'seed': 0, 'predictions_ref': 'predictions_base_untuned.jsonl'}, {'arm': 'treatment', 'metric': 'accuracy', 'value': 0.8335, 'evaluator_id': '25131a53fcdc110273727c96f2ec27d2ee549f02068efac718bed9e09fc9cbae', 'seed': 0, 'predictions_ref': 'predictions_lora_sft_grader.jsonl'}], 'comparisons': [{'metric': 'accuracy', 'arms': ['baseline', 'treatment']}]}
- evaluator_validation
- {'status': 'comparable', 'issues': [], 'comparisons': [{'metric': 'accuracy', 'status': 'comparable', 'arms': ['baseline', 'treatment'], 'evaluator_ids': ['25131a53fcdc110273727c96f2ec27d2ee549f02068efac718bed9e09fc9cbae'], 'missing_arms': []}]}
- feasibility
- {'status': 'unknown', 'problems': ['Re-projection required: dataset changed or was not recorded', 'Re-projection required: steps changed or was not recorded', 'Re-projection required: n_examples changed or was not recorded', 'Re-projection required: n_eval changed or was not recorded'], 'wall_seconds': None, 'gpu_hours': None, 'known_gpu_hours': 0, 'phases': {'setup': {'wall_seconds': 166.9, 'planned_units': 1, 'planned_samples': 0.0, 'gpu_hours': None}, 'training': {'wall_seconds': 572.8, 'planned_units': 320, 'planned_samples': 10240.0, 'gpu_hours': None}, 'evaluation': {'wall_seconds': 261.6, 'planned_units': 4000, 'planned_samples': 4000.0, 'gpu_hours': None}, 'recovery': {'wall_seconds': 1800, 'gpu_hours': None}}, 'generation_counts': None, 'generation_applicability': {'check': 'generation_audit', 'status': 'not_applicable', 'enforce': False, 'reasons': ['spec.generation_audit opts out and no feature it covers is true'], 'features': {'generated_training_data': False}}, 'record': {'config': {'base_model': 'Qwen/Qwen3.5-4B', 'arms': ['base_untuned', 'lora_sft_grader'], 'lora_rank': 32, 'lr': 0.0001, 'batch_size': 32, 'max_seq_len': 1024, 'steps': 20, 'n_eval': 200}, 'effective_config': {'base_model': 'Qwen/Qwen3.5-4B', 'arms': ['base_untuned', 'lora_sft_grader'], 'lora_rank': 32, 'lr': 0.0001, 'batch_size': 32, 'max_seq_len': 1024, 'steps': 150, 'n_eval': 2000}, 'primary_endpoint': 'pubmedqa_labeled_grading_accuracy', 'source': 'pilot.json/pilot2.log (pilot); full: full_attempt2.log (base eval), treat.log (treatment train+eval)', 'measurements': {'setup': {'seconds': 166.9, 'units': 1, 'planned_units': 1, 'samples': 0, 'gpu_count': None, 'allocation_source': None}, 'training': {'seconds': 268.5, 'units': 150, 'planned_units': 320, 'samples': 4800, 'gpu_count': None, 'allocation_source': None}, 'evaluation': {'seconds': 261.6, 'units': 4000, 'planned_units': 4000, 'samples': 4000, 'gpu_count': None, 'allocation_source': None}}, 'generation': None, 'recovery': {'seconds': 1800, 'gpu_count': None, 'allocation_source': None}}, 'recorded_at': 1793744733.6152964}
- feasibility_reported_verdict
- supported
- feasibility_required
- True
- generation_audit_validation
- {'status': 'not_applicable', 'reasons': ['spec.generation_audit opts out and no feature it covers is true'], 'applicability': {'check': 'generation_audit', 'status': 'not_applicable', 'enforce': False, 'reasons': ['spec.generation_audit opts out and no feature it covers is true'], 'features': {'generated_training_data': False}}}
- initialization_provenance
- {'version': 1, 'arms': [{'arm': 'treatment', 'base_model': 'Qwen/Qwen3.5-4B', 'lora_rank': 32, 'optimizer': 'adamw', 'source': 'server_response: TrainingClient.get_info()', 'evidence_ref': 'train_history.json', 'before_first_update': True, 'initial_output': {'batch_sha256': '2393c645b481af29e44e69fb04f6445ff98545c73eb1aaa75c7abdd69a039bd9', 'output_sha256': 'e009036d1059db074f375ce6c84e231ffdff3a285822743cba85c461ce01cfd1', 'n_values': 2809, 'verdict_nll': 8.556085480584038}}, {'arm': 'baseline', 'base_model': 'Qwen/Qwen3.5-4B', 'source': 'server_response: SamplingClient.get_base_model()', 'evidence_ref': 'full_attempt2.log', 'note': 'untuned base sampler'}]}
- launch
- {'experiment_id': 'exp_8088f9d3ee', 'context_status': 'snapshotted', 'superseded': False, 'mode': 'ordinary', 'purpose': 'Execute the selected saved experiment version.'}
- launch_instructions
- {'name': 'launch-instructions-6bb4c5736124.md', 'sha256': '6bb4c5736124181f1eb040cabc29379ca8f657a7ac7e7ebe82820fda596b0c2e', 'url': 'https://ta-01m6fva5db548f5skm214fepcr-8000-oah9l7x00jpo7186eb6cix5v0.w.modal.host/api/runs/run_03530094ad/evidence/6bb4c5736124181f1eb040cabc29379ca8f657a7ac7e7ebe82820fda596b0c2e'}
- reported_outcome_reason
- supported
- reported_verdict
- supported
- restoration_validation
- {'status': 'not_applicable', 'required': False, 'checks': [], 'reason': 'experiment_features: paired_training_arms, checkpoint_restore is false', 'applicability': 'not_applicable'}
Agent trace full trace with commands in Devin ↗
Details
- run
- run_03530094ad
- backend
- Devin
- session
- devin-a8c89320d63147058d3ff905aa9a591a
- experiment
- exp_8088f9d3ee
- created
- Nov 3, 21:12 UTC
- started
- Nov 3, 21:12 UTC
- finished
- Nov 3, 22:25 UTC
- duration
- 1h 13m
- GPU-h budget
- 1.5
- wall budget
- 120 min
- base model
- Qwen/Qwen3.5-4B
- training
- SFT
- dataset
- PubMedQA (pqa_artificial train, pqa_labeled eval)
- result
- final
- outcome reason
- insufficient evidence
Other runs of this idea
- run_86de83c72d no result 1d ago
- run_04595af10e no result 2d ago