Datasets:
Tasks:
Text Classification
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Tags:
structured-decisions
calibration
probabilistic-classification
system-one
workflow-evaluation
Synthetic
License:
Add ZhiPan2-4B (#70) to the fitted table
#71
by sandeep85 - opened
README.md
CHANGED
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@@ -146,30 +146,31 @@ zero-shot and their scores are not comparable with the table above.
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| 22 | Rev-gen1-mini (4.2B) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.7760 | 0.096 | 0.052 | 0.121 | 361 ms (B200, local) |
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| 23 | [soft-decider-421m](https://huggingface.co/winwinwinbb/soft-decider-421m) | specialist | 0.774 | – | – | 0.141 | 50 ms |
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| 24 | [Qwen3.5-4B-typed-decisions](https://huggingface.co/wozniakos10/Qwen3.5-4B-typed-decisions) (Qwen3.5-4B + LoRA, Clef head) | general, then fine-tuned on `train` | 0.7725 | 0.0992 | 0.0543 | 0.139 | – |
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| 48 | [Bekko System One v0
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**Quyet-1.0-Large, served by Decision Models, has the highest accuracy among zero-shot models (0.791). [meraGPT Decider 1](https://meragpt.com/models/state-decider-1?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=typed-decisions) is second on accuracy (0.768) and has the lowest KL (0.096) and Brier (0.052) of any zero-shot model.** It leads Jev on every question type (`noul` 0.840 vs
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0.775, `choice` 0.733 vs 0.720, `score` 0.739 vs 0.696), its distributions sit far
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- **Scored by us:** meraGPT Decider 1, TypeSafe Jev 1.13.0, Liquid AI d1, Baseten Mammoth 1 and Elephant 1, Featherless Simple Jev, the three Jeff models, the three rows served by Decision Models ([#38](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/38)), the Bekko and Adaptive Classifier rows, and the Prior and Uniform references.
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- **Scored by Hugging Face:** the rows linked to [#37](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/37), run on Hugging Face Jobs.
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- **Reported by an outside evaluator:** Qwen3.8-27B ([#60](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/60)), scored by adcostanza with the dataset's own scorer on SGLang; the full trace is public and rescores identically. SAP RPT 1.6 ([#49](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/49)), a self-run, unofficial evaluation of SAP's public Decisions API. The API answers from 300 `train` examples per workflow that SAP holds on its side, with no weight updates; those examples are SAP's description and could not be checked.
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- **Reported by the model's creator:** every other row, in its own discussion. The ten Rev-gen1 rows ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) come from private checkpoints whose predictions are not public, so they could not be rescored here. [serin-0.8b](https://huggingface.co/lambdasec/serin-0.8b) (lambdasec) has no discussion thread; it is a self-run evaluation with the benchmark's own scorer.
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## Reading a score
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| 22 | Rev-gen1-mini (4.2B) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.7760 | 0.096 | 0.052 | 0.121 | 361 ms (B200, local) |
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| 23 | [soft-decider-421m](https://huggingface.co/winwinwinbb/soft-decider-421m) | specialist | 0.774 | – | – | 0.141 | 50 ms |
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| 24 | [Qwen3.5-4B-typed-decisions](https://huggingface.co/wozniakos10/Qwen3.5-4B-typed-decisions) (Qwen3.5-4B + LoRA, Clef head) | general, then fine-tuned on `train` | 0.7725 | 0.0992 | 0.0543 | 0.139 | – |
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| 25 | ZhiPan2-4B (Qwen3.5-4B + typed decision head, closed weights) ([#70](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/70)) | specialist, per-question-type temperature calibration; [test predictions](https://huggingface.co/datasets/cayouccc/zhipan2-4b-td-predictions) public, rescored identically | 0.7710 | 0.1105 | 0.0587 | 0.1625 | – |
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| 26 | [lazydecider-0.8b](https://huggingface.co/rahulkumar0612/lazydecider-0.8b) (Qwen3.5-0.8B + LoRA, Clef joint-decision head) ([#47](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/47)) | specialist | 0.770 | 0.0938 | 0.0510 | 0.1454 | – |
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| 27 | [embeddinggemma-2-ft-typed-decision](https://huggingface.co/mrm8488/embeddinggemma-2-ft-typed-decision) (0.3B) ([#37](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/37)) | fine-tuned on `train` | 0.770 | 0.119 | 0.065 | 0.155 | – |
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| 28 | [Laya typed-decisions](https://huggingface.co/convaiinnovations/laya-typed-decisions) | fitted on `train` | 0.766 | – | – | – | – |
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| 29 | Rev-gen1-micro-lite (1.3B) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.7645 | 0.106 | 0.058 | 0.107 | 37 ms (B200, local) |
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| 30 | Rev-gen1-micro (1.9B) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.7645 | 0.150 | 0.080 | 0.223 | 52 ms (B200, local) |
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| 31 | Rev-gen1-UltraBERT-150M (150M) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.7630 | 0.173 | 0.092 | 0.228 | 82 ms (B200, local) |
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| 32 | Rev-gen1-UltraBERT-380M (378M) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.7620 | 0.144 | 0.075 | 0.203 | 82 ms (B200, local) |
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| 33 | [gemma3-270m-typed-decisions](https://huggingface.co/rony/gemma3-270m-typed-decisions) (Gemma 3 270M, full fine-tune) | specialist | 0.761 | 0.132 | 0.072 | 0.148 | 68 ms |
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| 34 | [nanoGentzen-v3](https://huggingface.co/Sagicc/nanoGentzen-v3) (4.93M) ([#59](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/59)) | weights trained on synthetic logic data; rules and calibrated distributions built for this benchmark's workflows | 0.7585 | 0.207 | 0.100 | 0.065 | 18 ms |
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| 35 | [SafeDecide-140M](https://huggingface.co/yotambr/safedecide-140m) (mmBERT-small, 140M) ([#39](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/39)) | general, then fine-tuned on `train` | 0.754 | 0.126 | 0.069 | 0.147 | 80 ms (1 CPU thread) |
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| 36 | [Seb-9B](https://huggingface.co/ironbcc/seb-9b) (Qwen3.5-9B, v1) ([#13](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/13)) | general, then fitted on `train`, one question per request | 0.754 | 0.349 | 0.131 | 0.031 | – |
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| 37 | [tasksource-decider-nano](https://huggingface.co/tasksource/tasksource-decider-nano) (149M cross-encoder, `v5`) ([#45](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/45)) | general; `train` is 0.5% of its training mix | 0.7515 | 0.1125 | 0.0621 | 0.125 | 37 ms (A30, shared) |
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| 38 | Rev-gen1-nano (752M) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.7515 | 0.117 | 0.064 | 0.094 | 52 ms (B200, local) |
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| 39 | [ProKope-421M-8K](https://huggingface.co/ProKope-AI/ProKope-421M-8K) (421M, 8K context) | specialist | 0.7185 | – | 0.385 | – | 43 ms |
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| 40 | [serin-0.8b](https://huggingface.co/lambdasec/serin-0.8b) (Qwen3.5-0.8B, 0.8B) | general, then trained on `train` | 0.7165 | 0.9577 | 0.1502 | 0.1122 | – |
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| 41 | [gemma3-270m-typed-decisions](https://huggingface.co/rony/gemma3-270m-typed-decisions) (Gemma 3 270M, full fine-tune) | general, fine-tuned on `train` | 0.702 | 0.156 | 0.091 | 0.128 | 68 ms |
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| 42 | SAP RPT 1.6 via the SAP Decisions API (`/api/systemone`), [evaluation](https://huggingface.co/datasets/tomgutt/rpt-1.6-typed-decisions-evaluation) ([#49](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/49)) | in-context: 300 provider-held `train` examples per workflow, no weight updates; closed API | 0.672 | 0.646 | 0.151 | 0.019 | 656 ms (p50, API round trip) |
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| 43 | [Bekko System One v0 400M](https://huggingface.co/hotchpotch/bekko-system-one-v0-400m), scored by us | trained on `train` and other data | 0.668 | 0.214 | 0.113 | 0.143 | 808 ms |
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| 44 | [vega-08b-public-intents](https://huggingface.co/nandakishorm/vega-08b-public-intents) (0.8B) ([#37](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/37)) | specialist (bundled typed-decisions adapter active) | 0.663 | 0.435 | 0.191 | 0.074 | – |
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| 45 | ModernBERT-base (149M), ours | specialist, fitted per workflow | 0.646 | 0.223 | 0.119 | 0.179 | 349 ms |
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| 46 | Rev-gen1-EmbeddingGemma-2-Frozen (272M) ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) | general, trained on a mix including filtered `train`; weights and predictions private | 0.6015 | 0.248 | 0.142 | 0.042 | 92 ms (B200, local) |
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| 47 | MiniLM-L6 (22M), ours | specialist, fitted per workflow | 0.587 | 0.262 | 0.143 | 0.108 | 22 ms |
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| 48 | [Bekko System One v0 68M](https://huggingface.co/hotchpotch/bekko-system-one-v0-68m), scored by us | trained on `train` and other data | 0.537 | 0.293 | 0.160 | 0.116 | 176 ms |
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| 49 | [Bekko System One v0 17M](https://huggingface.co/hotchpotch/bekko-system-one-v0-17m), scored by us | trained on `train` and other data | 0.483 | 0.344 | 0.203 | 0.136 | 33 ms |
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**Quyet-1.0-Large, served by Decision Models, has the highest accuracy among zero-shot models (0.791). [meraGPT Decider 1](https://meragpt.com/models/state-decider-1?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=typed-decisions) is second on accuracy (0.768) and has the lowest KL (0.096) and Brier (0.052) of any zero-shot model.** It leads Jev on every question type (`noul` 0.840 vs
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0.775, `choice` 0.733 vs 0.720, `score` 0.739 vs 0.696), its distributions sit far
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- **Scored by us:** meraGPT Decider 1, TypeSafe Jev 1.13.0, Liquid AI d1, Baseten Mammoth 1 and Elephant 1, Featherless Simple Jev, the three Jeff models, the three rows served by Decision Models ([#38](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/38)), the Bekko and Adaptive Classifier rows, and the Prior and Uniform references.
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- **Scored by Hugging Face:** the rows linked to [#37](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/37), run on Hugging Face Jobs.
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- **Reported by an outside evaluator:** Qwen3.8-27B ([#60](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/60)), scored by adcostanza with the dataset's own scorer on SGLang; the full trace is public and rescores identically. SAP RPT 1.6 ([#49](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/49)), a self-run, unofficial evaluation of SAP's public Decisions API. The API answers from 300 `train` examples per workflow that SAP holds on its side, with no weight updates; those examples are SAP's description and could not be checked.
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- **Reported by the model's creator:** every other row, in its own discussion. The ten Rev-gen1 rows ([#64](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/64)) come from private checkpoints whose predictions are not public, so they could not be rescored here. [serin-0.8b](https://huggingface.co/lambdasec/serin-0.8b) (lambdasec) has no discussion thread; it is a self-run evaluation with the benchmark's own scorer. ZhiPan2-4B ([#70](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/70)) keeps its weights closed, but its full test predictions are [public](https://huggingface.co/datasets/cayouccc/zhipan2-4b-td-predictions) and rescore identically with the dataset's scorer.
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## Reading a score
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