kev-4b preview, decision-v7 recipe (transfer 0.790 dev / 0.806 locked; held-out pairs 0.73)
Browse files- README.md +15 -15
- adapter_model.safetensors +1 -1
- head.pt +2 -2
- provenance.json +23 -19
- result.json +1717 -669
- train.log +316 -274
- training_config.json +9 -4
- training_metrics.json +7 -7
README.md
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- task: { type: text-classification, name: typed decision (choice / noul / score) }
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dataset: { type: mixed, name: "decision-v4 development (1,204 records; ten trained public sources + programmatic policy pairs)" }
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metrics:
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- { type: accuracy, value: 0.
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- { type: expected_calibration_error, value: 0.
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- task: { type: text-classification, name: typed decision, out-of-domain }
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dataset: { type: mixed, name: "transfer-v4 development (764 records; six never-trained sources + held-out policy structures)" }
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metrics:
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---
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# kev-4b — research preview
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`kev-4b` is a **decision model**: one document (the *state*) and a set of typed questions in, a probability distribution per question out, in one forward pass. No text generation. It is a LoRA adapter (r=16) plus a pointer head on `Qwen/Qwen3-4B-Base`, serving TypeSafe's public `/v1/systemone` contract.
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**Research preview, not a versioned release.** It is the best 4B checkpoint under a frozen, checksummed protocol after ~
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- Hub: `jaredpalmer/kev-4b` (this repo; trial `
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- Code, suites, every trial with hashes and paired bootstraps: [github.com/jaredpalmer/kev](https://github.com/jaredpalmer/kev) — `PLAN.md`, `runs/leaderboard.md`
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## Results (same frozen items for every row)
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| | kev-0.5b | kev-0.6b preview | **kev-4b preview** | Jev |
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|---|---|---|---|---|
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| in-distribution accuracy (decision-v4 dev, 1,200 q) | 0.712 | 0.805 | **0.
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| out-of-domain accuracy (transfer-v4 dev, 560 q) | 0.575 | 0.598 | **0.
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| out-of-domain Brier | 0.50 | 0.521 | **0.
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| confident errors out of domain (p ≥ 0.9 and wrong) | – | 5.2% |
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| held-out policy structures, both siblings correct | – | 0.11 | 0.
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| option-order flip rate | 0.21 | 0.02 | 0.
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Per-source out-of-domain accuracy (kev-4b / Jev): QNLI 0.89 / 0.93, SciQ 0.99 / 0.99, TweetEval-offensive 0.
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Seeds:
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**Locked test, one exploratory read** (`runs/locked/kev-4b-preview-ungated/`, labelled ungated because the
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## What we learned building it
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- task: { type: text-classification, name: typed decision (choice / noul / score) }
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dataset: { type: mixed, name: "decision-v4 development (1,204 records; ten trained public sources + programmatic policy pairs)" }
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metrics:
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- { type: accuracy, value: 0.854 }
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- { type: expected_calibration_error, value: 0.065, name: "ECE, raw probabilities" }
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- task: { type: text-classification, name: typed decision, out-of-domain }
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dataset: { type: mixed, name: "transfer-v4 development (764 records; six never-trained sources + held-out policy structures)" }
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metrics:
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- { type: accuracy, value: 0.790 }
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- { type: brier_score, value: 0.328 }
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---
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# kev-4b — research preview
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`kev-4b` is a **decision model**: one document (the *state*) and a set of typed questions in, a probability distribution per question out, in one forward pass. No text generation. It is a LoRA adapter (r=16) plus a pointer head on `Qwen/Qwen3-4B-Base`, serving TypeSafe's public `/v1/systemone` contract.
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**Research preview, not a versioned release.** It is the best 4B checkpoint under a frozen, checksummed protocol after ~40 controlled 4B trials, and the first kev whose out-of-domain accuracy is within ten points of Jev on the same items. This checkpoint clears the release screen we set in advance (held-out policy pairs 0.73 both-correct, screen 70%), but the other two seeds of the same recipe do not (0.62, 0.67), and our rule is every seed; so it stays a preview.
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- Hub: `jaredpalmer/kev-4b` (this repo; trial `v7-rc3/01-trial-1`)
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- Code, suites, every trial with hashes and paired bootstraps: [github.com/jaredpalmer/kev](https://github.com/jaredpalmer/kev) — `PLAN.md`, `runs/leaderboard.md`
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## Results (same frozen items for every row)
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| | kev-0.5b | kev-0.6b preview | **kev-4b preview** | Jev |
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|---|---|---|---|---|
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| in-distribution accuracy (decision-v4 dev, 1,200 q) | 0.712 | 0.805 | **0.854** | 0.845 |
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| out-of-domain accuracy (transfer-v4 dev, 560 q) | 0.575 | 0.598 | **0.790** | 0.857 |
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| out-of-domain Brier | 0.50 | 0.521 | **0.328** | 0.211 |
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| confident errors out of domain (p ≥ 0.9 and wrong) | – | 5.2% | 8.2% | 3.7% |
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| held-out policy structures, both siblings correct | – | 0.11 | 0.73 | 0.86 |
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| option-order flip rate | 0.21 | 0.02 | 0.06 | 0.00 |
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Per-source out-of-domain accuracy (kev-4b / Jev): QNLI 0.89 / 0.93, SciQ 0.99 / 0.99, TweetEval-offensive 0.75 / 0.81, PAWS 0.72 / 0.79, MMLU 0.65 / 0.90, Emotion 0.66 / 0.59, deadline (3-level date arithmetic) 0.53 / 0.93, (A and B) or not C 0.97 / 0.97, if A then not B else C 0.88 / 0.78.
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Seeds: three seeds on decision-v7: transfer 0.773 / **0.790** / 0.770, held-out pairs 0.62 / **0.73** / 0.67; this checkpoint is seed 1, selected on development transfer accuracy. Trained on `decision-v7` (10k public records + 896 policy records over nine template families incl. four ordinal Score threshold families + 1,680 records from 60 random rule structures with negation anywhere); development/test items are byte-identical to v4, so every number here is comparable with earlier previews.
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**Locked test, one exploratory read** (`runs/locked/kev-4b-v7-preview-ungated/`, labelled ungated because the screen is not met on every seed): in-distribution **0.856** (Brier 0.211), out-of-domain **0.806** (Brier 0.294, confident errors 6.6%, held-out pairs 0.66). This partition will not be read again for this checkpoint.
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## What we learned building it
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adapter_model.safetensors
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| 416 |
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| 417 |
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| 418 |
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| 419 |
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| 420 |
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| 428 |
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| 429 |
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| 430 |
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| 431 |
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| 440 |
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| 441 |
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| 442 |
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| 453 |
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| 454 |
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| 582 |
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| 583 |
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| 594 |
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|
@@ -596,95 +1046,167 @@
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|
| 596 |
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| 597 |
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| 598 |
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| 621 |
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| 632 |
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| 633 |
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| 634 |
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| 635 |
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| 637 |
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| 643 |
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| 644 |
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| 645 |
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| 655 |
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| 657 |
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| 665 |
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| 666 |
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| 668 |
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| 669 |
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| 678 |
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| 689 |
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| 690 |
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|
@@ -692,34 +1214,52 @@
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|
| 692 |
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| 693 |
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| 694 |
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|
| 709 |
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| 710 |
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| 711 |
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| 714 |
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| 715 |
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| 724 |
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| 725 |
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|
@@ -736,297 +1276,513 @@
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|
| 736 |
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| 737 |
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| 738 |
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| 752 |
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| 753 |
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| 880 |
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| 905 |
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| 974 |
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| 997 |
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| 998 |
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| 1007 |
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| 1008 |
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| 1009 |
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| 1020 |
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| 1021 |
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| 1030 |
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| 1031 |
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|
| 1032 |
}
|
|
@@ -1034,95 +1790,167 @@
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|
| 1034 |
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|
| 1035 |
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|
| 1036 |
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| 1037 |
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| 1038 |
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|
| 1045 |
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| 1046 |
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| 1047 |
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| 1050 |
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| 1051 |
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| 1052 |
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| 1055 |
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| 1056 |
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| 1057 |
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| 1058 |
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| 1059 |
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| 1060 |
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| 1061 |
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| 1062 |
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| 1064 |
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| 1067 |
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| 1068 |
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| 1069 |
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|
| 1070 |
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|
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| 1128 |
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|
@@ -1130,290 +1958,506 @@
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| 1130 |
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| 1360 |
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train.log
CHANGED
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| 1 |
device=cuda trainable params=34.3M
|
| 2 |
+
12576 training requests (holdout=[]), questions by type {'score': 3448, 'noul': 5224, 'choice': 6904}
|
| 3 |
+
ep0 step 10/3144 loss 1.923 kl 0.000 anchor 0.000 0.115s/rec
|
| 4 |
+
ep0 step 20/3144 loss 1.955 kl 0.000 anchor 0.000 0.104s/rec
|
| 5 |
+
ep0 step 30/3144 loss 1.836 kl 0.000 anchor 0.000 0.096s/rec
|
| 6 |
+
ep0 step 40/3144 loss 1.603 kl 0.000 anchor 0.000 0.091s/rec
|
| 7 |
+
ep0 step 50/3144 loss 1.912 kl 0.000 anchor 0.000 0.089s/rec
|
| 8 |
+
ep0 step 60/3144 loss 1.877 kl 0.000 anchor 0.000 0.087s/rec
|
| 9 |
+
ep0 step 70/3144 loss 1.917 kl 0.000 anchor 0.000 0.086s/rec
|
| 10 |
+
ep0 step 80/3144 loss 1.750 kl 0.000 anchor 0.000 0.086s/rec
|
| 11 |
+
ep0 step 90/3144 loss 1.381 kl 0.000 anchor 0.000 0.084s/rec
|
| 12 |
+
ep0 step 100/3144 loss 1.739 kl 0.000 anchor 0.000 0.083s/rec
|
| 13 |
+
ep0 step 110/3144 loss 1.481 kl 0.000 anchor 0.000 0.083s/rec
|
| 14 |
+
ep0 step 120/3144 loss 1.663 kl 0.000 anchor 0.000 0.082s/rec
|
| 15 |
+
ep0 step 130/3144 loss 1.701 kl 0.000 anchor 0.000 0.082s/rec
|
| 16 |
+
ep0 step 140/3144 loss 1.566 kl 0.000 anchor 0.000 0.082s/rec
|
| 17 |
+
ep0 step 150/3144 loss 1.299 kl 0.000 anchor 0.000 0.082s/rec
|
| 18 |
+
ep0 step 160/3144 loss 1.138 kl 0.000 anchor 0.000 0.081s/rec
|
| 19 |
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ep0 step 170/3144 loss 1.178 kl 0.000 anchor 0.000 0.081s/rec
|
| 20 |
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ep0 step 180/3144 loss 1.114 kl 0.000 anchor 0.000 0.080s/rec
|
| 21 |
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ep0 step 190/3144 loss 1.150 kl 0.000 anchor 0.000 0.081s/rec
|
| 22 |
+
ep0 step 200/3144 loss 0.915 kl 0.000 anchor 0.000 0.080s/rec
|
| 23 |
+
ep0 step 210/3144 loss 1.179 kl 0.000 anchor 0.000 0.080s/rec
|
| 24 |
+
ep0 step 220/3144 loss 0.817 kl 0.000 anchor 0.000 0.080s/rec
|
| 25 |
+
ep0 step 230/3144 loss 0.852 kl 0.000 anchor 0.000 0.080s/rec
|
| 26 |
+
ep0 step 240/3144 loss 0.547 kl 0.000 anchor 0.000 0.080s/rec
|
| 27 |
+
ep0 step 250/3144 loss 0.881 kl 0.000 anchor 0.000 0.079s/rec
|
| 28 |
+
ep0 step 260/3144 loss 0.791 kl 0.000 anchor 0.000 0.079s/rec
|
| 29 |
+
ep0 step 270/3144 loss 0.886 kl 0.000 anchor 0.000 0.080s/rec
|
| 30 |
+
ep0 step 280/3144 loss 0.763 kl 0.000 anchor 0.000 0.080s/rec
|
| 31 |
+
ep0 step 290/3144 loss 0.738 kl 0.000 anchor 0.000 0.080s/rec
|
| 32 |
+
ep0 step 300/3144 loss 0.673 kl 0.000 anchor 0.000 0.080s/rec
|
| 33 |
+
ep0 step 310/3144 loss 0.937 kl 0.000 anchor 0.000 0.081s/rec
|
| 34 |
+
ep0 step 320/3144 loss 0.900 kl 0.000 anchor 0.000 0.081s/rec
|
| 35 |
+
ep0 step 330/3144 loss 0.663 kl 0.000 anchor 0.000 0.081s/rec
|
| 36 |
+
ep0 step 340/3144 loss 0.715 kl 0.000 anchor 0.000 0.080s/rec
|
| 37 |
+
ep0 step 350/3144 loss 0.685 kl 0.000 anchor 0.000 0.080s/rec
|
| 38 |
+
ep0 step 360/3144 loss 0.644 kl 0.000 anchor 0.000 0.080s/rec
|
| 39 |
+
ep0 step 370/3144 loss 0.879 kl 0.000 anchor 0.000 0.080s/rec
|
| 40 |
+
ep0 step 380/3144 loss 0.771 kl 0.000 anchor 0.000 0.080s/rec
|
| 41 |
+
ep0 step 390/3144 loss 0.550 kl 0.000 anchor 0.000 0.080s/rec
|
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+
ep0 step 400/3144 loss 0.629 kl 0.000 anchor 0.000 0.080s/rec
|
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+
ep0 step 410/3144 loss 0.603 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 420/3144 loss 0.670 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 430/3144 loss 0.525 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 440/3144 loss 0.782 kl 0.000 anchor 0.000 0.081s/rec
|
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ep0 step 450/3144 loss 0.638 kl 0.000 anchor 0.000 0.081s/rec
|
| 48 |
+
ep0 step 460/3144 loss 0.600 kl 0.000 anchor 0.000 0.081s/rec
|
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+
ep0 step 470/3144 loss 0.648 kl 0.000 anchor 0.000 0.081s/rec
|
| 50 |
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ep0 step 480/3144 loss 0.359 kl 0.000 anchor 0.000 0.081s/rec
|
| 51 |
+
ep0 step 490/3144 loss 0.663 kl 0.000 anchor 0.000 0.081s/rec
|
| 52 |
+
ep0 step 500/3144 loss 0.725 kl 0.000 anchor 0.000 0.081s/rec
|
| 53 |
+
ep0 step 510/3144 loss 0.563 kl 0.000 anchor 0.000 0.081s/rec
|
| 54 |
+
ep0 step 520/3144 loss 0.600 kl 0.000 anchor 0.000 0.081s/rec
|
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+
ep0 step 530/3144 loss 0.742 kl 0.000 anchor 0.000 0.081s/rec
|
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ep0 step 540/3144 loss 0.496 kl 0.000 anchor 0.000 0.081s/rec
|
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ep0 step 550/3144 loss 0.444 kl 0.000 anchor 0.000 0.081s/rec
|
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ep0 step 560/3144 loss 0.641 kl 0.000 anchor 0.000 0.081s/rec
|
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ep0 step 570/3144 loss 0.522 kl 0.000 anchor 0.000 0.081s/rec
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ep0 step 580/3144 loss 0.408 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 590/3144 loss 0.471 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 600/3144 loss 0.877 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 610/3144 loss 0.564 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 620/3144 loss 0.773 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 630/3144 loss 0.519 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 640/3144 loss 0.495 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 650/3144 loss 0.587 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 660/3144 loss 0.514 kl 0.000 anchor 0.000 0.080s/rec
|
| 69 |
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ep0 step 670/3144 loss 0.793 kl 0.000 anchor 0.000 0.080s/rec
|
| 70 |
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ep0 step 680/3144 loss 0.393 kl 0.000 anchor 0.000 0.080s/rec
|
| 71 |
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ep0 step 690/3144 loss 0.582 kl 0.000 anchor 0.000 0.080s/rec
|
| 72 |
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ep0 step 700/3144 loss 0.631 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 710/3144 loss 0.736 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 720/3144 loss 0.378 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 730/3144 loss 0.631 kl 0.000 anchor 0.000 0.080s/rec
|
| 76 |
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ep0 step 740/3144 loss 0.714 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 750/3144 loss 0.484 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 760/3144 loss 0.344 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 770/3144 loss 0.850 kl 0.000 anchor 0.000 0.080s/rec
|
| 80 |
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ep0 step 780/3144 loss 0.722 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 790/3144 loss 0.595 kl 0.000 anchor 0.000 0.080s/rec
|
| 82 |
+
ep0 step 800/3144 loss 0.443 kl 0.000 anchor 0.000 0.080s/rec
|
| 83 |
+
ep0 step 810/3144 loss 0.691 kl 0.000 anchor 0.000 0.080s/rec
|
| 84 |
+
ep0 step 820/3144 loss 0.433 kl 0.000 anchor 0.000 0.080s/rec
|
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ep0 step 830/3144 loss 0.613 kl 0.000 anchor 0.000 0.079s/rec
|
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ep0 step 840/3144 loss 0.703 kl 0.000 anchor 0.000 0.079s/rec
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ep0 step 850/3144 loss 0.628 kl 0.000 anchor 0.000 0.079s/rec
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ep0 step 890/3144 loss 0.478 kl 0.000 anchor 0.000 0.079s/rec
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ep0 step 900/3144 loss 0.569 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 910/3144 loss 0.674 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 920/3144 loss 0.536 kl 0.000 anchor 0.000 0.080s/rec
|
| 95 |
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ep0 step 930/3144 loss 0.575 kl 0.000 anchor 0.000 0.080s/rec
|
| 96 |
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ep0 step 940/3144 loss 0.527 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 950/3144 loss 0.391 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 960/3144 loss 0.742 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 970/3144 loss 0.481 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 980/3144 loss 0.357 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 990/3144 loss 0.722 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 1000/3144 loss 0.550 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 1010/3144 loss 0.453 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 1020/3144 loss 0.457 kl 0.000 anchor 0.000 0.079s/rec
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ep0 step 1030/3144 loss 0.816 kl 0.000 anchor 0.000 0.080s/rec
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ep0 step 1040/3144 loss 0.463 kl 0.000 anchor 0.000 0.079s/rec
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ep0 step 1050/3144 loss 0.630 kl 0.000 anchor 0.000 0.079s/rec
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ep0 step 1060/3144 loss 0.465 kl 0.000 anchor 0.000 0.079s/rec
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saved /runs/v7-rc3/01-trial-1/checkpoint
|
training_config.json
CHANGED
|
@@ -4,13 +4,15 @@
|
|
| 4 |
"n_per_source": 1000,
|
| 5 |
"epochs": 2,
|
| 6 |
"lr": 5e-05,
|
|
|
|
|
|
|
| 7 |
"lora": 16,
|
| 8 |
"accum": 2,
|
| 9 |
"holdout": "",
|
| 10 |
"perm_kl": 0.0,
|
| 11 |
"perm_frac": 0.3,
|
| 12 |
"ord_w": 0.0,
|
| 13 |
-
"suite": "/root/evals/
|
| 14 |
"train_sources": "",
|
| 15 |
"device": "cuda",
|
| 16 |
"batch": 4,
|
|
@@ -27,10 +29,13 @@
|
|
| 27 |
"p_none_pair": 0.25,
|
| 28 |
"synthetic_repeat": 1,
|
| 29 |
"public_frac": 1.0,
|
| 30 |
-
"
|
| 31 |
-
"
|
|
|
|
|
|
|
|
|
|
| 32 |
},
|
| 33 |
-
"suite_sha256": "
|
| 34 |
"base_revision": "906bfd4b4dc7f14ee4320094d8b41684abff8539",
|
| 35 |
"ordinal_objective": "ranked_probability_score",
|
| 36 |
"holdout": []
|
|
|
|
| 4 |
"n_per_source": 1000,
|
| 5 |
"epochs": 2,
|
| 6 |
"lr": 5e-05,
|
| 7 |
+
"head_lr": 0.0,
|
| 8 |
+
"weight_decay": 0.01,
|
| 9 |
"lora": 16,
|
| 10 |
"accum": 2,
|
| 11 |
"holdout": "",
|
| 12 |
"perm_kl": 0.0,
|
| 13 |
"perm_frac": 0.3,
|
| 14 |
"ord_w": 0.0,
|
| 15 |
+
"suite": "/root/evals/v7/decision-v7",
|
| 16 |
"train_sources": "",
|
| 17 |
"device": "cuda",
|
| 18 |
"batch": 4,
|
|
|
|
| 29 |
"p_none_pair": 0.25,
|
| 30 |
"synthetic_repeat": 1,
|
| 31 |
"public_frac": 1.0,
|
| 32 |
+
"anchor": "",
|
| 33 |
+
"anchor_w": 0.0,
|
| 34 |
+
"anchor_sources": "",
|
| 35 |
+
"out": "/runs/v7-rc3/01-trial-1/checkpoint",
|
| 36 |
+
"seed": 1
|
| 37 |
},
|
| 38 |
+
"suite_sha256": "a8f50e481b7d90b97da049e0ff6a01cee2f1ed204aed61a8265af0edbb5514d2",
|
| 39 |
"base_revision": "906bfd4b4dc7f14ee4320094d8b41684abff8539",
|
| 40 |
"ordinal_objective": "ranked_probability_score",
|
| 41 |
"holdout": []
|
training_metrics.json
CHANGED
|
@@ -1,14 +1,14 @@
|
|
| 1 |
{
|
| 2 |
-
"wall_seconds":
|
| 3 |
-
"records_seen":
|
| 4 |
-
"requested_records":
|
| 5 |
"truncated_records": 0,
|
| 6 |
"rejected_records": 0,
|
| 7 |
-
"optimizer_steps":
|
| 8 |
-
"forward_tokens":
|
| 9 |
-
"peak_device_bytes":
|
| 10 |
"device": "cuda",
|
| 11 |
"dtype": "bf16",
|
| 12 |
"batch": 4,
|
| 13 |
-
"peak_rss_bytes":
|
| 14 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"wall_seconds": 2378.645946741104,
|
| 3 |
+
"records_seen": 30530,
|
| 4 |
+
"requested_records": 25152,
|
| 5 |
"truncated_records": 0,
|
| 6 |
"rejected_records": 0,
|
| 7 |
+
"optimizer_steps": 3144,
|
| 8 |
+
"forward_tokens": 5860024,
|
| 9 |
+
"peak_device_bytes": 23007304704,
|
| 10 |
"device": "cuda",
|
| 11 |
"dtype": "bf16",
|
| 12 |
"batch": 4,
|
| 13 |
+
"peak_rss_bytes": 25029832704
|
| 14 |
}
|