165 lines
4.2 KiB
JSON
165 lines
4.2 KiB
JSON
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{
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"schema_version": 1,
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"model": "ConeML/coneml-810m-alpha",
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"scope": "Aggregate results from ConeML internal held-out instruments and the stated public-benchmark subsets. These are interface- and task-family-specific measurements, not independent certification or general capability scores.",
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"bf16": {
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"task_family_certification": {
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"ckpt": "ConeML/coneml-810m-alpha",
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"decoding": "greedy, rep_penalty 1.15, frame 'Question:/Answer:'",
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"by_category": {
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"add-1d": {
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"correct": 70,
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"n": 71,
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"acc": 0.9859
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},
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"add-2d-carry": {
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"correct": 266,
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"n": 500,
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"acc": 0.532
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},
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"comparison": {
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"correct": 363,
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"n": 500,
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"acc": 0.726
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},
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"missing-addend": {
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"correct": 358,
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"n": 500,
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"acc": 0.716
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},
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"missing-factor": {
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"correct": 89,
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"n": 500,
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"acc": 0.178
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},
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"mul-1d": {
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"correct": 44,
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"n": 45,
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"acc": 0.9778
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},
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"mul-2dx1d": {
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"correct": 487,
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"n": 500,
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"acc": 0.974
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},
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"sub-borrow": {
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"correct": 455,
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"n": 500,
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"acc": 0.91
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},
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"two-step": {
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"correct": 395,
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"n": 500,
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"acc": 0.79
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},
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"which-bigger": {
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"correct": 285,
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"n": 300,
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"acc": 0.95
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}
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}
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},
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"executed_single_function_writing": {
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"ckpt": "ConeML/coneml-810m-alpha",
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"passed": 207,
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"n": 300,
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"rate": 0.69,
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"by_family": {
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"code_arith": "18/24",
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"code_branch": "11/31",
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"code_count": "34/35",
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"code_dedup": "20/26",
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"code_filter": "2/25",
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"code_maxmin": "16/23",
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"code_range": "16/20",
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"code_reduce": "15/33",
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"code_reverse": "15/20",
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"code_strings": "60/63"
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},
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"scoring": "generated function exec'd against held-out tests; expected values from verified reference"
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},
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"basic_code_screen": {
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"ckpt": "ConeML/coneml-810m-alpha",
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"by_type": {
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"bash": "1/5",
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"explain": "manual/10",
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"script": "0/10",
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"sql": "1/10"
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}
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},
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"designated_refusal_probe": {
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"ckpt": "ConeML/coneml-810m-alpha",
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"refusals": "17/17",
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"contrast_answers": "5/5",
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"over_refusal": 0
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},
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"everyday_reasoning_screen": {
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"n": 20,
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"automatic_score": "6/20",
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"manual_score": "11/20",
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"adjudication": "manual adjudication; criterion: correct final choice, quantity, or agent regardless of phrasing"
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},
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"public_benchmarks": {
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"model": {
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"context": 8192,
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"generation_budget": 256,
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"gsm8k": {
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"n": 200,
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"correct": 12,
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"acc": 0.06,
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"truncation_rate": 0.01
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},
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"humaneval": {
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"n": 164,
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"passed": 5,
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"pass@1": 0.0305,
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"truncation_rate": 0.024
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}
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},
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"pretrained_base_reference": {
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"context": 8192,
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"generation_budget": 256,
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"gsm8k": {
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"n": 200,
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"correct": 7,
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"acc": 0.035,
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"truncation_rate": 0.315
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},
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"humaneval": {
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"n": 164,
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"passed": 0,
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"pass@1": 0.0,
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"truncation_rate": 0.665
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}
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}
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},
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"raw_completion_spot_check": {
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"n": 12,
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"seed": 188,
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"temperature": 0.8,
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"repetition_penalty": 1.15,
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"repeated_4gram_rate": 0.0,
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"distinct_2gram_rate": 0.9714,
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"mean_words": 44.8
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},
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"conversation_probe": {
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"probe": "conversation-v2",
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"score": {
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"correct": 8,
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"n": 8,
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"accuracy": 1.0
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},
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"gate": {
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"threshold": "at least 7/8 overall and turn 8 must pass",
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"passed": true
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},
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"scope": "One scripted eight-turn dialogue; not a general conversation benchmark."
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}
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},
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"row_level_evidence": {
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"public_subset": "representative-samples.json",
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"private_full_rows": "retained by ConeML",
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"hash_commitment": "PRIVATE_EVIDENCE_SHA256SUMS.txt"
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}
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}
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