WP31: 5-seed routing summary, statistics, ranking controller result
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
26 changed files +1,850 −34
modified
FAILURES.md
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@@ -10,3 +10,4 @@ | ||
| 10 | 10 | | 2026-10-30 | Joint fine-tuning reference (backbone unfrozen, lr 3e-4, answer-span loss): validation loss rose from 0.4005 to 0.472 at every budget after 500 steps — the backbone degraded under the narrower objective and the large learning rate. | M4M64a `experiments/logs/p4_joint_mixed_w64.log` | Not a usable upper reference as run; a low-lr variant is deferred (not required by the pre-registered comparison). | |
| 11 | 11 | | 2026-10-30 | v2 tiny backbone (5.6M, 15k planned steps) overfit the 23k-item train split: validation loss (all tokens) 0.246 at step 6k → 0.282 at step 9k. Run stopped at step 9,300; the step-5,000 checkpoint (val 0.249) is used as the frozen v2 backbone. | `experiments/logs/p4_tiny_backbone_v2.log`, run `p4_tiny_backbone_v2_seed01_*` (state: stopped) | 42 epochs of a small synthetic set is too many; schedule not re-run (the checkpoint is adequate as a frozen comparator). | |
| 12 | 12 | | 2026-10-30 | Killed to free nodes for the 5-seed matrix: the degraded joint-finetune reference (M4M64a) and the v1 dense-writes run on the slow m4mn node (superseded by the v2 matrix `p4v2_dense`). | manifests remain in `experiments/runs/` on the nodes (state: running → killed) | — | |
| 13 | +| 2026-10-30 | Ranking-loss controller (D12: pairwise + listwise on top of Huber/BCE/NLL, editor-unseen labels): calibration sign accuracy fell to 45 %, captured fraction −8 %; on dev-iid the locked policy (λ=0.3, κ=0.5) edits 0.07 tokens and matches budget 0 (0.4333 vs 0.4334); λ=0 is worse (+1.3 %). | `experiments/runs/controller_v1rank_seed01_*`, `results/raw/routing_v1rank.json` | Within-state ranking is not learnable from these labels at this scale; H3 null stands. | | |
modified
PROGRESS.md
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| 9 | 9 | | 2026-10-29 | 4 learnability (backbone) | done | `p4_tiny_backbone.yaml` → run `p4_tiny_backbone_seed01_20261029232626` (2.1M params, 6k steps, char-level) | exact match (greedy): dev_iid arith 16.8 %, dev_template 13.7 %, dev_depth 3.0 %, compose 2.4 % (first-600-item subsets, arith-heavy) | PASS (weak backbone, usable comparator) | stronger v2 backbone (5.6M, 15k steps) running | |
| 10 | 10 | | 2026-10-29 | 4 learnability (overfit) | done | `p4_overfit64_b8.yaml` → run `p4_overfit64_b8_seed01_20261029235111` | 64 items, budget 8, frozen backbone: train loss 0.347 → 0.0024 in 200 steps; dev loss rises 0.73 → 1.36 (expected) | PASS (gradient path + capacity) | — | |
| 11 | 11 | | 2026-10-29 | 4 learnability (generalisation, v1 backbone) | done | zero-U scaled (laptop), U std 0.2 / 0.5 (M4M64c / M2U64), budget-8-only w64/w128 and mixed w128 lr 3e-3 (M2U64 / M4M64c / M4M64a) | after 2000 steps (U std 0.2): dev-iid loss −1.4 % at budgets 1–2, +1.7 % at budget 8; exact match dev-iid 43.8 → 45.8 % (b2), template/depth unchanged, compose 2.3 → 3.0 %; zero-U + scale alone: −0.6 %; lr 3e-3 w128: collapse to inert edits; global-recurrence adapter (same recipe): loss ≥ backbone at every budget, EM 43.8 → 45.8 % (b8) | PASS (weak, learnable; mechanism effect ≈ 1 %) | decisive 5-seed matrix on v2 backbone | |
| 12 | −| 2026-10-30 | 4 decisive matrix (v2 backbone, 5 seeds × {PRISME, global recurrence, dense}) | running | `scripts/launch_seed_matrix.sh` → 15 runs on M2U64/M4M64c/M4M64a/M5M36/M4BP48/M4BP36 | — | — | aggregate with `scripts/make_tables.py` | | |
| 12 | +| 2026-10-30 | 4 decisive matrix (v2 backbone, 5 seeds × {PRISME, global recurrence}; dense running) | done (PRISME, GR) | `scripts/launch_seed_matrix.sh`; `scripts/statistics.py` → `results/analyzed/{seed_matrix_v2,statistics_v2}.json` | dev-iid loss vs budget 0 (0.4621): PRISME −2.1/−2.8/−3.0/−1.0 % at b=1/2/4/8 (seed SD ≤ 0.003); GR −3.6/−4.1/−3.7/−3.3 %; EM dev-iid 37.7 → PRISME 39.6 (b2, +1.9 pp, t-CI [1.6, 2.2]) vs GR 39.6 (b2) / 40.0 (b8); PRISME − GR at b2 +0.06 pp [−0.53, +0.65]; OOD regimes unchanged (≤ 1 pp) | H1 weak PASS (< 3 pp prereg minimum); sparse ≤ global at every budget | dense seeds pending (M4BP36 lost; relaunched) | | |
| 13 | +| 2026-10-30 | 6 controller on v2 editors (4 seeds) | done | `scripts/run_stage_cd.sh` → `results/analyzed/routing_seeds_v2.json` | locked controller: dev-iid loss +0.5 % ± 1.1 vs budget 0 (0.05–4.3 edits/token); best fixed schedule −4.0 %; oracle b8 −15.0 %; calib sign acc 0.50–0.63, captured 0.30–0.52 on calib audit but no transfer to dev rollouts | H3 null replicated across seeds | ranking-loss variant (D12) | | |
| 13 | 14 | | 2026-10-30 | 5 counterfactual labels + oracle audit (tiny) | done | `labels_p4.yaml` → run `labels_p4_seed01_20261030000543` (80,632 train + 20,040 calib labels; 4,778 + 1,308 exhaustive-audit states); `evaluation.label_analysis` | gains: mean 0.004, 42 % positive, 37 % harmful; variance 86–89 % between states vs 11–14 % within state (action identity); 37 % of states have all 24 actions positive, 29 % all negative; one-step oracle 0.0166 nats/state = 0.0098 (perfect stop, random action) + 0.0067 (action selection); random action 0.0004 | PASS (oracle margin exists; action choice is ≈40 % of it) | controller fit | |
| 14 | 15 | | 2026-10-30 | 6 controller (tiny) | partial | `controller_p4.yaml` → `controller_p4_seed01_20261030000716` (z features): calib sign acc 49 %, captured fraction −3 %; sweep: best (λ=0.1, κ=0.5) loss −0.1 % with 0.01 edits/token; `controller_p4_hent.yaml` (h + backbone entropy): sign acc 59–60 % at 1–2k steps then overfits (early stopping added) | controller with z-only features = chance; h+entropy features predict the sign above chance but capture ≤ 5 % of the oracle opportunity | OPEN (H3 null so far at tiny scale) | rerun with early stopping; more labels | |
| 15 | 16 | | 2026-10-30 | 7 inference engine + latency (tiny) | done | `tests/integration/test_cache_equivalence.py` (5 tests pass); `evaluation.latency` on the laptop MPS → `results/raw/latency_p4_*_mps.json` | batch-1 decode: 2.8 ms/token (budget 0) → 5.3 (1 edit) → 19.3 ms (8 edits); dense 8 edits 17.3 ms (not slower than sparse at this scale); controller call ≈ +2.9 ms even with 0 edits | PASS (equivalence); dispatch overhead dominates at tiny scale (brief §13.6 confirmed) | re-measure at 103M | |
| 16 | 17 | | 2026-10-29 | 8 pilot (Stage A) | running | M3U96a: `pretrain_103m.yaml` (run `pretrain103m_seed01_*`); M3U96b: `pretrain_enlarged_102m.yaml` | 14.8k tok/s, 196.6M tokens planned (~3.7 h each) | — | editor/controller stages after completion | |
| 17 | 18 | | 2026-10-30 | 5/6 routing evaluation (tiny v1 editor, dev-iid, 640 items / 3,417 answer tokens) | done | `evaluation.routing` → `results/raw/routing_controller_p4_hent_seed01_20261030002015_dev_iid.json` | budget 0: 0.4334; uniform b1 0.4301 (−0.8 %), random b1 0.4305, fixed pair b1 0.4306; b8 schedules +0.6 to +2.8 %; entropy router ≥ budget 0; norm router (thr 0.2) 0.4309; learned controller (locked λ=0.3) 0.4404 (+1.6 %) and worse at every λ; greedy one-step oracle 0.4025 (b1) → 0.3666 (b8, 2.26 edits/token, −15 %); two-step oracle gain 0.034 vs one-step 0.0233 vs greedy-then-best 0.0337 (myopia regret ≈ 0) | H2 null (uniform = random = pair); H3 null (controller < no routing on dev) at this scale; oracle opportunity large | labels from a split unseen by the editor (D11); 5-seed v2 matrix | |
| 19 | +| 2026-10-30 | 6 ranking-loss controller (D12, tiny v1 editor, editor-unseen labels) | done | `controller_v1rank.yaml` → `results/raw/routing_v1rank.json` | locked λ=0.3 κ=0.5: dev-iid loss 0.4333 vs 0.4334 (0.07 edits/token); λ=0: +1.3 % | H3 null stands | — | | |
modified
configs/experiments/routing_v1rank.yaml
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@@ -1,7 +1,7 @@ | ||
| 1 | 1 | seed: 1 |
| 2 | 2 | mode: prisme |
| 3 | 3 | model: from_checkpoint |
| 4 | −checkpoint: CONTROLLER_CKPT | |
| 4 | +checkpoint: experiments/runs/controller_v1rank_seed01_20261030005431/checkpoint | |
| 5 | 5 | data: |
| 6 | 6 | kind: synthetic |
| 7 | 7 | tokenizer: char |
modified
experiments/logs/controller_v1rank.log
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@@ -33,3 +33,13 @@ step 1999 loss 3.74421 gain 0.00241 harm 0.5247 | ||
| 33 | 33 | restored controller from step 750 (calibration score -0.01242) |
| 34 | 34 | sweep {'lambda': 0.0, 'kappa': 0.0, 'loss': 0.44029377250626134, 'edits_per_token': 3.0255041518386716, 'extra_ops_ratio': 0.9985018783334029} |
| 35 | 35 | sweep {'lambda': 0.0, 'kappa': 0.5, 'loss': 0.43276796307003795, 'edits_per_token': 1.5634638196915778, 'extra_ops_ratio': 0.5107896924725914} |
| 36 | +sweep {'lambda': 0.01, 'kappa': 0.0, 'loss': 0.4399834968865554, 'edits_per_token': 2.7941874258600237, 'extra_ops_ratio': 0.9065133996422746} | |
| 37 | +sweep {'lambda': 0.01, 'kappa': 0.5, 'loss': 0.4311416666702868, 'edits_per_token': 1.3849347568208779, 'extra_ops_ratio': 0.44641059432024066} | |
| 38 | +sweep {'lambda': 0.03, 'kappa': 0.0, 'loss': 0.4382320236622368, 'edits_per_token': 2.3718861209964412, 'extra_ops_ratio': 0.7466290384566374} | |
| 39 | +sweep {'lambda': 0.03, 'kappa': 0.5, 'loss': 0.43146511272462096, 'edits_per_token': 1.120403321470937, 'extra_ops_ratio': 0.3504910203202905} | |
| 40 | +sweep {'lambda': 0.1, 'kappa': 0.0, 'loss': 0.43422956681619196, 'edits_per_token': 1.2627520759193358, 'extra_ops_ratio': 0.371382664672562} | |
| 41 | +sweep {'lambda': 0.1, 'kappa': 0.5, 'loss': 0.4304978969116935, 'edits_per_token': 0.5195729537366548, 'extra_ops_ratio': 0.15240548768501688} | |
| 42 | +sweep {'lambda': 0.3, 'kappa': 0.0, 'loss': 0.4298561159543437, 'edits_per_token': 0.3309608540925267, 'extra_ops_ratio': 0.09634915280596641} | |
| 43 | +sweep {'lambda': 0.3, 'kappa': 0.5, 'loss': 0.4300144485165923, 'edits_per_token': 0.11684460260972716, 'extra_ops_ratio': 0.034015740434752945} | |
| 44 | +selected {'lambda': 0.3, 'kappa': 0.5, 'loss': 0.4300144485165923, 'edits_per_token': 0.11684460260972716, 'extra_ops_ratio': 0.034015740434752945, 'loss_reduction': 0.001048727250466841, 'reduction_per_ops': 0.03083064596163796} | |
| 45 | +run controller_v1rank_seed01_20261030005431 | |
added
experiments/logs/routing_v1rank.log
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| 1 | +{"policy": "budget0", "loss": 0.43343788690653534, "edits_per_token": 0.0, "extra_ops_ratio": 0.0, "n_tokens": 3417} | |
| 2 | +/Users/simon-pierreboucher/Desktop/Recherche-UQO/ia/prisme-slm/training/train_editor.py:57: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /Users/runner/work/pytorch/pytorch/torch/csrc/utils/tensor_numpy.cpp:214.) | |
| 3 | + return torch.from_numpy(acts).to(device), torch.from_numpy(np.ascontiguousarray(b)).to(device) | |
| 4 | +{"policy": "random_forced", "budget": 1, "loss": 0.43049107206331766, "edits_per_token": 1.0, "extra_ops_ratio": 0.33739269034430613, "n_tokens": 3417} | |
| 5 | +{"policy": "uniform", "budget": 1, "loss": 0.430082754325476, "edits_per_token": 1.0, "extra_ops_ratio": 0.2911194881431394, "n_tokens": 3417} | |
| 6 | +{"policy": "fixed_pair", "budget": 1, "loss": 0.4306084942950259, "edits_per_token": 1.0, "extra_ops_ratio": 0.38326141294904154, "n_tokens": 3417} | |
| 7 | +{"policy": "random_forced", "budget": 2, "loss": 0.43129151572879726, "edits_per_token": 2.0, "extra_ops_ratio": 0.6752437784687831, "n_tokens": 3417} | |
| 8 | +{"policy": "uniform", "budget": 2, "loss": 0.43061076446970825, "edits_per_token": 2.0, "extra_ops_ratio": 0.5822389762862789, "n_tokens": 3417} | |
| 9 | +{"policy": "fixed_pair", "budget": 2, "loss": 0.43226337237493456, "edits_per_token": 2.0, "extra_ops_ratio": 0.7665228258980831, "n_tokens": 3417} | |
| 10 | +{"policy": "random_forced", "budget": 4, "loss": 0.4350665061488499, "edits_per_token": 4.0, "extra_ops_ratio": 1.3500830851558498, "n_tokens": 3417} | |
| 11 | +{"policy": "uniform", "budget": 4, "loss": 0.43226772879940184, "edits_per_token": 4.0, "extra_ops_ratio": 1.1644779525725577, "n_tokens": 3417} | |
| 12 | +{"policy": "fixed_pair", "budget": 4, "loss": 0.43608775067685257, "edits_per_token": 4.0, "extra_ops_ratio": 1.5330456517961661, "n_tokens": 3417} | |
| 13 | +{"policy": "random_forced", "budget": 8, "loss": 0.44534724575753865, "edits_per_token": 8.0, "extra_ops_ratio": 2.6992224028210283, "n_tokens": 3417} | |
| 14 | +{"policy": "uniform", "budget": 8, "loss": 0.4360636224654602, "edits_per_token": 8.0, "extra_ops_ratio": 2.3289559051451154, "n_tokens": 3417} | |
| 15 | +{"policy": "fixed_pair", "budget": 8, "loss": 0.4454028259636821, "edits_per_token": 8.0, "extra_ops_ratio": 3.0660913035923323, "n_tokens": 3417} | |
| 16 | +{"policy": "entropy", "threshold": 0.1, "budget": 8, "loss": 0.44345039856653656, "edits_per_token": 2.893473807433421, "extra_ops_ratio": 0.9313065950585138, "n_tokens": 3417} | |
| 17 | +{"policy": "entropy", "threshold": 0.5, "budget": 8, "loss": 0.44244280132174246, "edits_per_token": 2.097453906935909, "extra_ops_ratio": 0.6750847836283169, "n_tokens": 3417} | |
| 18 | +{"policy": "entropy", "threshold": 1.0, "budget": 8, "loss": 0.4375149400603328, "edits_per_token": 1.1785191688615744, "extra_ops_ratio": 0.3794397201180842, "n_tokens": 3417} | |
| 19 | +{"policy": "entropy", "threshold": 2.0, "budget": 8, "loss": 0.43457157094819804, "edits_per_token": 0.20749195200468246, "extra_ops_ratio": 0.06636437945523596, "n_tokens": 3417} | |
| 20 | +{"policy": "norm", "threshold": 0.02, "budget": 8, "loss": 0.4431566372928056, "edits_per_token": 7.994146912496342, "extra_ops_ratio": 2.576118717076383, "n_tokens": 3417} | |
| 21 | +{"policy": "norm", "threshold": 0.05, "budget": 8, "loss": 0.4419520246658124, "edits_per_token": 7.054141059408838, "extra_ops_ratio": 2.2736114108984604, "n_tokens": 3417} | |
| 22 | +{"policy": "norm", "threshold": 0.1, "budget": 8, "loss": 0.4397261778374042, "edits_per_token": 4.717588527948493, "extra_ops_ratio": 1.5199677263884506, "n_tokens": 3417} | |
| 23 | +{"policy": "norm", "threshold": 0.2, "budget": 8, "loss": 0.430901125784258, "edits_per_token": 1.0491659350307287, "extra_ops_ratio": 0.33984092665514054, "n_tokens": 3417} | |
| 24 | +{"policy": "controller_locked", "lam": 0.3, "kap": 0.5, "budget": 8, "loss": 0.43332059026845965, "edits_per_token": 0.06613988879133743, "extra_ops_ratio": 0.01925461050499103, "n_tokens": 3417} | |
| 25 | +{"policy": "controller", "lam": 0.0, "kap": 0.5, "budget": 8, "loss": 0.4392198074760582, "edits_per_token": 1.4641498390400935, "extra_ops_ratio": 0.48109084149707576, "n_tokens": 3417} | |
| 26 | +{"policy": "controller", "lam": 0.01, "kap": 0.5, "budget": 8, "loss": 0.43936958569757484, "edits_per_token": 1.3075797483172373, "extra_ops_ratio": 0.42456216117182355, "n_tokens": 3417} | |
| 27 | +{"policy": "controller", "lam": 0.03, "kap": 0.5, "budget": 8, "loss": 0.438084998115448, "edits_per_token": 1.0398009950248757, "extra_ops_ratio": 0.3312630400798598, "n_tokens": 3417} | |
| 28 | +{"policy": "controller", "lam": 0.1, "kap": 0.5, "budget": 8, "loss": 0.4354970293991183, "edits_per_token": 0.4433713784021071, "extra_ops_ratio": 0.13166276062654758, "n_tokens": 3417} | |
| 29 | +{"policy": "controller", "lam": 0.3, "kap": 0.5, "budget": 8, "loss": 0.43332059026845965, "edits_per_token": 0.06613988879133743, "extra_ops_ratio": 0.01925461050499103, "n_tokens": 3417} | |
| 30 | +{"policy": "oracle1_greedy", "budget": 1, "diagnostic": true, "loss": 0.4025459464804867, "edits_per_token": 0.5237366003062787, "extra_ops_ratio": 0.19226168855956283, "n_tokens": 653} | |
| 31 | +{"policy": "oracle1_greedy", "budget": 2, "diagnostic": true, "loss": 0.390496985653093, "edits_per_token": 0.9509954058192955, "extra_ops_ratio": 0.34655941646277993, "n_tokens": 653} | |
| 32 | +{"policy": "oracle1_greedy", "budget": 4, "diagnostic": true, "loss": 0.37995706181431255, "edits_per_token": 1.5313935681470139, "extra_ops_ratio": 0.552776494398599, "n_tokens": 653} | |
| 33 | +{"policy": "oracle1_greedy", "budget": 8, "diagnostic": true, "loss": 0.3665898426751083, "edits_per_token": 2.2664624808575806, "extra_ops_ratio": 0.8196839220125861, "n_tokens": 653} | |
| 34 | +{"policy": "oracle_two_step", "diagnostic": true, "one_step_gain": 0.023339285247627347, "two_step_gain": 0.03395615775009681, "greedy_then_best_gain": 0.03374234835306803, "n_tokens": 174} | |
| 35 | +wrote results/raw/routing_v1rank.json | |
| 36 | +RANK_DONE | |
added
experiments/runs/controller_v1rank_seed01_20261030005431/checkpoint/checkpoint.json
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| 1 | +{ | |
| 2 | + "config": { | |
| 3 | + "name": "tiny_p4", | |
| 4 | + "vocab_size": 128, | |
| 5 | + "d_model": 192, | |
| 6 | + "n_layers": 4, | |
| 7 | + "n_heads": 6, | |
| 8 | + "n_kv_heads": 2, | |
| 9 | + "ffn_width": 512, | |
| 10 | + "max_seq_len": 320, | |
| 11 | + "rope_theta": 10000.0, | |
| 12 | + "norm_eps": 1e-05, | |
| 13 | + "tie_embeddings": true, | |
| 14 | + "init_std": 0.02, | |
| 15 | + "use_workspace": true, | |
| 16 | + "w": 64, | |
| 17 | + "ffn_w": 192, | |
| 18 | + "n_slots": 16, | |
| 19 | + "n_editor_blocks": 2, | |
| 20 | + "n_editor_heads": 2, | |
| 21 | + "r_max": 8, | |
| 22 | + "eta_max": 0.25, | |
| 23 | + "clip_c": 1.0, | |
| 24 | + "clip_eps": 1e-06, | |
| 25 | + "readout_zero_init": false, | |
| 26 | + "readout_init_std": 0.2, | |
| 27 | + "readout_scale": 5.251033782958984, | |
| 28 | + "controller_hidden": 0, | |
| 29 | + "ctrl_input": "h", | |
| 30 | + "ctrl_use_entropy": true, | |
| 31 | + "lambda_cost": 0.3, | |
| 32 | + "kappa_risk": 0.5, | |
| 33 | + "dense_writes": false | |
| 34 | + }, | |
| 35 | + "saved_at": "2026-10-30T00:57:23-0400", | |
| 36 | + "run_id": "controller_v1rank_seed01_20261030005431", | |
| 37 | + "parent": "experiments/runs/p4_editor_v1_Ustd02_seed01_20261029235050/checkpoint", | |
| 38 | + "selected": { | |
| 39 | + "lambda": 0.3, | |
| 40 | + "kappa": 0.5, | |
| 41 | + "loss": 0.4300144485165923, | |
| 42 | + "edits_per_token": 0.11684460260972716, | |
| 43 | + "extra_ops_ratio": 0.034015740434752945, | |
| 44 | + "loss_reduction": 0.001048727250466841, | |
| 45 | + "reduction_per_ops": 0.03083064596163796 | |
| 46 | + }, | |
| 47 | + "locked": true, | |
| 48 | + "weights_sha256": "64570e628212ba370db86265ffaa23f655bfee6e58120829c5bbe5881c7aadd9" | |
| 49 | +} | |
| \ No newline at end of file | ||
modified
experiments/runs/controller_v1rank_seed01_20261030005431/manifest.json
+136 −3
@@ -9,10 +9,143 @@ | ||
| 9 | 9 | "python": "3.12.13", |
| 10 | 10 | "torch": "2.15.0", |
| 11 | 11 | "command": "/Users/simon-pierreboucher/Desktop/Recherche-UQO/ia/prisme-slm/training/train_controller.py --config configs/experiments/controller_v1rank.yaml --device mps", |
| 12 | − "state": "running", | |
| 13 | − "wall_seconds": 0.02, | |
| 12 | + "state": "completed", | |
| 13 | + "wall_seconds": 171.86, | |
| 14 | 14 | "device": "mps", |
| 15 | 15 | "checkpoint_parent": "experiments/runs/p4_editor_v1_Ustd02_seed01_20261029235050/checkpoint", |
| 16 | 16 | "labels_train": "experiments/runs/labels_v1ctrl_seed01_20261030004018/labels_train.pt", |
| 17 | − "labels_calib": "experiments/runs/labels_v1ctrl_seed01_20261030004018/labels_calib.pt" | |
| 17 | + "labels_calib": "experiments/runs/labels_v1ctrl_seed01_20261030004018/labels_calib.pt", | |
| 18 | + "finished_at": "2026-10-30T00:57:23-0400", | |
| 19 | + "eval_train": { | |
| 20 | + "huber": 0.0022109991413126954, | |
| 21 | + "sign_acc": 0.5578782919208451, | |
| 22 | + "harm_brier": 0.18087974557421105, | |
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experiments/runs/controller_v2s1_seed01_20261030005758/checkpoint/checkpoint.json
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| 1 | +{ | |
| 2 | + "config": { | |
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added
experiments/runs/controller_v2s1_seed01_20261030005758/config.yaml
+67 −0
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| 1 | +experiment: | |
| 2 | + name: controller_v2s1 | |
| 3 | + seed: 1 | |
| 4 | + mode: prisme | |
| 5 | + model: from_checkpoint | |
| 6 | + checkpoint: experiments/runs/p4v2_prisme_seed01_20261030001749/checkpoint | |
| 7 | + labels: | |
| 8 | + train: experiments/runs/labels_v2s1_seed01_20261030005712/labels_train.pt | |
| 9 | + calib: experiments/runs/labels_v2s1_seed01_20261030005712/labels_calib.pt | |
| 10 | + train: | |
| 11 | + steps: 2000 | |
| 12 | + lr: 0.001 | |
| 13 | + weight_decay: 0.01 | |
| 14 | + alpha: 1.0 | |
| 15 | + beta: 0.5 | |
| 16 | + gamma: 0.1 | |
| 17 | + huber_delta: 0.1 | |
| 18 | + log_every: 100 | |
| 19 | + eval_every: 250 | |
| 20 | + seq_len: 320 | |
| 21 | + lambda_grid: | |
| 22 | + - 0.0 | |
| 23 | + - 0.01 | |
| 24 | + - 0.03 | |
| 25 | + - 0.1 | |
| 26 | + - 0.3 | |
| 27 | + kappa_grid: | |
| 28 | + - 0.0 | |
| 29 | + - 0.5 | |
| 30 | + sweep_batches: 10 | |
| 31 | + max_budget: 8 | |
| 32 | + selection_rule: max_loss_reduction_per_ops | |
| 33 | + model_overrides: | |
| 34 | + ctrl_input: h | |
| 35 | + ctrl_use_entropy: true | |
| 36 | +model: | |
| 37 | + name: tiny_p4v2 | |
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| 47 | + tie_embeddings: true | |
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| 50 | + w: 64 | |
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| 64 | + ctrl_use_entropy: true | |
| 65 | + lambda_cost: 0.0 | |
| 66 | + kappa_risk: 0.0 | |
| 67 | + dense_writes: false | |
added
experiments/runs/controller_v2s1_seed01_20261030005758/manifest.json
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| \ No newline at end of file | ||
added
experiments/runs/controller_v2s1_seed01_20261030005758/metrics.jsonl
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| 5 | +{"step": 300, "loss": 0.14486049115657806, "gain": 0.003396645188331604, "harm": 0.6058646440505981, "nll": -1.6146845817565918, "t": 21.57} | |
| 6 | +{"step": 400, "loss": 0.07704775035381317, "gain": 0.0020318725146353245, "harm": 0.5852528810501099, "nll": -2.176105499267578, "t": 26.95} | |
| 7 | +{"step": 499, "calib_huber": 0.0015250327621141929, "calib_sign_acc": 0.5629365433199583, "calib_harm_brier": 0.17094168093994974, "calib_harm_ece": 0.022884827107191086, "calib_n_labels": 26916, "calib_oracle_opportunity_per_state": 0.01836320621989056, "calib_regret_per_state": 0.01282272375101014, "calib_captured_fraction": 0.30171650868240585, "calib_top1_match": 0.0547112462006079, "calib_n_audit_states": 1645, "t": 33.86} | |
| 8 | +{"step": 500, "loss": 0.001370161771774292, "gain": 0.001527803367935121, "harm": 0.5307777523994446, "nll": -2.6554653644561768, "t": 33.92} | |
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| 12 | +{"step": 800, "loss": -0.019962161779403687, "gain": 0.0013843975029885769, "harm": 0.48733922839164734, "nll": -2.6501615047454834, "t": 51.84} | |
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| 15 | +{"step": 1000, "loss": -0.04631441831588745, "gain": 0.0013401865726336837, "harm": 0.4754399061203003, "nll": -2.853745460510254, "t": 64.4} | |
| 16 | +{"step": 1100, "loss": -0.07637041807174683, "gain": 0.0010725471656769514, "harm": 0.4387507736682892, "nll": -2.9681835174560547, "t": 69.79} | |
| 17 | +{"step": 1200, "loss": -0.06496578454971313, "gain": 0.0010426120134070516, "harm": 0.4698534905910492, "nll": -3.0093514919281006, "t": 75.21} | |
| 18 | +{"step": 1249, "calib_huber": 0.0011220869855551932, "calib_sign_acc": 0.6217491454896715, "calib_harm_brier": 0.15860497322598402, "calib_harm_ece": 0.02261553332209587, "calib_n_labels": 26916, "calib_oracle_opportunity_per_state": 0.01836320621989056, "calib_regret_per_state": 0.010739420540064664, "calib_captured_fraction": 0.41516637065089457, "calib_top1_match": 0.06504559270516717, "calib_n_audit_states": 1645, "t": 79.37} | |
| 19 | +{"step": 1300, "loss": -0.1207217276096344, "gain": 0.0005600811564363539, "harm": 0.4300370216369629, "nll": -3.3630030155181885, "t": 82.05} | |
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| 22 | +{"step": 1500, "loss": -0.06804871559143066, "gain": 0.000664825551211834, "harm": 0.5305606126785278, "nll": -3.3399384021759033, "t": 94.21} | |
| 23 | +{"step": 1600, "loss": -0.07556450366973877, "gain": 0.001154533470980823, "harm": 0.5068498849868774, "nll": -3.3014397621154785, "t": 99.54} | |
| 24 | +{"step": 1700, "loss": -0.10204572975635529, "gain": 0.001108089811168611, "harm": 0.4906119704246521, "nll": -3.48459792137146, "t": 104.94} | |
| 25 | +{"step": 1749, "calib_huber": 0.0009797979088112332, "calib_sign_acc": 0.6669638876504681, "calib_harm_brier": 0.16354970610288794, "calib_harm_ece": 0.049120619893074036, "calib_n_labels": 26916, "calib_oracle_opportunity_per_state": 0.01836320621989056, "calib_regret_per_state": 0.012027452854399986, "calib_captured_fraction": 0.34502435411457977, "calib_top1_match": 0.08875379939209727, "calib_n_audit_states": 1645, "t": 109.14} | |
| 26 | +{"step": 1800, "loss": -0.11715850234031677, "gain": 0.0008175690891221166, "harm": 0.4343639016151428, "nll": -3.3515801429748535, "t": 111.91} | |
| 27 | +{"step": 1900, "loss": -0.1207641214132309, "gain": 0.0008810321451164782, "harm": 0.4911242127418518, "nll": -3.672072649002075, "t": 117.51} | |
| 28 | +{"step": 1999, "loss": -0.11400634050369263, "gain": 0.0009010079083964229, "harm": 0.47006553411483765, "nll": -3.499401092529297, "t": 122.79} | |
| 29 | +{"step": 1999, "calib_huber": 0.0009146865885242485, "calib_sign_acc": 0.4517387427552385, "calib_harm_brier": 0.15814475145820417, "calib_harm_ece": 0.018627993762493134, "calib_n_labels": 26916, "calib_oracle_opportunity_per_state": 0.01836320621989056, "calib_regret_per_state": 0.01151024432892495, "calib_captured_fraction": 0.37318983454766497, "calib_top1_match": 0.07963525835866261, "calib_n_audit_states": 1645, "t": 124.31} | |
| 30 | +{"event": "restored_best_calibration_checkpoint", "step": 1250, "score": -0.010739420540064664, "t": 124.31} | |
added
experiments/runs/labels_v2s1_seed01_20261030005712/config.yaml
+58 −0
@@ -0,0 +1,58 @@ | ||
| 1 | +experiment: | |
| 2 | + name: labels_v2s1 | |
| 3 | + seed: 1 | |
| 4 | + mode: prisme | |
| 5 | + model: from_checkpoint | |
| 6 | + checkpoint: experiments/runs/p4v2_prisme_seed01_20261030001749/checkpoint | |
| 7 | + use_policy: false | |
| 8 | + data: | |
| 9 | + kind: synthetic | |
| 10 | + tokenizer: char | |
| 11 | + splits_dir: data/splits/synthetic_v1 | |
| 12 | + loss_span: answer | |
| 13 | + collect: | |
| 14 | + batch_size: 32 | |
| 15 | + seq_len: 320 | |
| 16 | + max_prefix: 3 | |
| 17 | + audit_every: 4 | |
| 18 | + partitions: | |
| 19 | + train: | |
| 20 | + split: ctrl_train | |
| 21 | + n_batches: 300 | |
| 22 | + stream_seed: 11 | |
| 23 | + calib: | |
| 24 | + split: calib | |
| 25 | + n_batches: 40 | |
| 26 | + stream_seed: 12 | |
| 27 | +model: | |
| 28 | + name: tiny_p4v2 | |
| 29 | + vocab_size: 128 | |
| 30 | + d_model: 256 | |
| 31 | + n_layers: 6 | |
| 32 | + n_heads: 8 | |
| 33 | + n_kv_heads: 4 | |
| 34 | + ffn_width: 768 | |
| 35 | + max_seq_len: 320 | |
| 36 | + rope_theta: 10000.0 | |
| 37 | + norm_eps: 1.0e-05 | |
| 38 | + tie_embeddings: true | |
| 39 | + init_std: 0.02 | |
| 40 | + use_workspace: true | |
| 41 | + w: 64 | |
| 42 | + ffn_w: 192 | |
| 43 | + n_slots: 16 | |
| 44 | + n_editor_blocks: 2 | |
| 45 | + n_editor_heads: 2 | |
| 46 | + r_max: 8 | |
| 47 | + eta_max: 0.25 | |
| 48 | + clip_c: 1.0 | |
| 49 | + clip_eps: 1.0e-06 | |
| 50 | + readout_zero_init: false | |
| 51 | + readout_init_std: 0.2 | |
| 52 | + readout_scale: 38.47460174560547 | |
| 53 | + controller_hidden: 0 | |
| 54 | + ctrl_input: z | |
| 55 | + ctrl_use_entropy: false | |
| 56 | + lambda_cost: 0.0 | |
| 57 | + kappa_risk: 0.0 | |
| 58 | + dense_writes: false | |
added
experiments/runs/labels_v2s1_seed01_20261030005712/manifest.json
+40 −0
@@ -0,0 +1,40 @@ | ||
| 1 | +{ | |
| 2 | + "run_id": "labels_v2s1_seed01_20261030005712", | |
| 3 | + "name": "labels_v2s1", | |
| 4 | + "seed": 1, | |
| 5 | + "code_commit": "unknown", | |
| 6 | + "config_sha256": "d8a7c72237e220d4d2c97a848283a4500bd5af90fdd38e416f3c63cbf99d54af", | |
| 7 | + "started_at": "2026-10-30T00:57:12-0400", | |
| 8 | + "host": "MacStudonpierre", | |
| 9 | + "python": "3.12.14", | |
| 10 | + "torch": "2.15.0", | |
| 11 | + "command": "/Users/simon-pierreboucher/wp31/prisme-slm/training/collect_interventions.py --config configs/experiments/labels_v2s1.yaml --device mps", | |
| 12 | + "state": "completed", | |
| 13 | + "wall_seconds": 44.65, | |
| 14 | + "device": "mps", | |
| 15 | + "checkpoint_parent": "experiments/runs/p4v2_prisme_seed01_20261030001749/checkpoint", | |
| 16 | + "checkpoint_sha256": "63501504cc2f44e41c51c3c2ec941160a997e2e5035167f0cf79e8de7dc00d37", | |
| 17 | + "finished_at": "2026-10-30T00:57:57-0400", | |
| 18 | + "partitions": { | |
| 19 | + "train": { | |
| 20 | + "file": "experiments/runs/labels_v2s1_seed01_20261030005712/labels_train.pt", | |
| 21 | + "n_states": 49965, | |
| 22 | + "n_labels": 199860, | |
| 23 | + "mean_gain": 0.004881912376731634, | |
| 24 | + "frac_positive": 0.3325177729129791, | |
| 25 | + "frac_harm": 0.5166516304016113, | |
| 26 | + "seconds": 39.4, | |
| 27 | + "n_audit_batches": 75 | |
| 28 | + }, | |
| 29 | + "calib": { | |
| 30 | + "file": "experiments/runs/labels_v2s1_seed01_20261030005712/labels_calib.pt", | |
| 31 | + "n_states": 6729, | |
| 32 | + "n_labels": 26916, | |
| 33 | + "mean_gain": 0.005064019002020359, | |
| 34 | + "frac_positive": 0.33912914991378784, | |
| 35 | + "frac_harm": 0.5117030739784241, | |
| 36 | + "seconds": 5.2, | |
| 37 | + "n_audit_batches": 10 | |
| 38 | + } | |
| 39 | + } | |
| 40 | +} | |
| \ No newline at end of file | ||
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experiments/runs/labels_v2s1_seed01_20261030005712/metrics.jsonl
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paper/appendix/failures.tex
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@@ -18,4 +18,6 @@ | ||
| 18 | 18 | \textbf{date}: 2026-10-30; \textbf{what failed}: v2 tiny backbone (5.6M, 15k planned steps) overfit the 23k-item train split: validation loss (all tokens) 0.246 at step 6k $\rightarrow$ 0.282 at step 9k. Run stopped at step 9,300; the step-5,000 checkpoint (val 0.249) is used as the frozen v2 backbone.; \textbf{evidence}: \texttt{experiments/logs/p4\_tiny\_backbone\_v2.log}, run \texttt{p4\_tiny\_backbone\_v2\_seed01\_*} (state: stopped); \textbf{resolution}: 42 epochs of a small synthetic set is too many; schedule not re-run (the checkpoint is adequate as a frozen comparator). |
| 19 | 19 | \item |
| 20 | 20 | \textbf{date}: 2026-10-30; \textbf{what failed}: Killed to free nodes for the 5-seed matrix: the degraded joint-finetune reference (M4M64a) and the v1 dense-writes run on the slow m4mn node (superseded by the v2 matrix \texttt{p4v2\_dense}).; \textbf{evidence}: manifests remain in \texttt{experiments/runs/} on the nodes (state: running $\rightarrow$ killed) |
| 21 | +\item | |
| 22 | + \textbf{date}: 2026-10-30; \textbf{what failed}: Ranking-loss controller (D12: pairwise + listwise on top of Huber/BCE/NLL, editor-unseen labels): calibration sign accuracy fell to 45 \%, captured fraction --8 \%; on dev-iid the locked policy ($\lambda$=0.3, $\kappa$=0.5) edits 0.07 tokens and matches budget 0 (0.4333 vs 0.4334); $\lambda$=0 is worse (+1.3 \%).; \textbf{evidence}: \texttt{experiments/runs/controller\_v1rank\_seed01\_*}, \texttt{results/raw/routing\_v1rank.json}; \textbf{resolution}: Within-state ranking is not learnable from these labels at this scale; H3 null stands. | |
| 21 | 23 | \end{itemize} |
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paper/main.log
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| 1336 | −(./sections/limitations.tex [21]) (./sections/conclusion.tex) | |
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| 1354 | 1354 | i Ning, Ning Ding, and |
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@@ -103,15 +103,24 @@ over \vtwoctrlseeds{} seeds the locked controller changes the dev-iid loss by \v | ||
| 103 | 103 | \vtwoctrlrelsd{}) while editing a small fraction of tokens, the best fixed schedule lowers it by |
| 104 | 104 | \vtwobestfixedrel{}\,\% and the greedy oracle by \vtwooraclerel{}\,\%; the controller beats the frozen backbone |
| 105 | 105 | on \vtwoctrlbetter{} of \vtwoctrlseeds{} seeds and never approaches the fixed schedules at any cost. |
| 106 | +(v) Adding within-state ranking losses (pairwise on the logged candidates, listwise on the exhaustive audits; | |
| 107 | +Appendix~\ref{app:failures}) did not change the picture: the locked policy edits 0.07 tokens and matches | |
| 108 | +budget 0 (0.4333 vs 0.4334), and every smaller penalty is worse. | |
| 106 | 109 | \input{tables/routing.tex} |
| 107 | 110 | \input{tables/controller.tex} |
| 108 | 111 | \input{tables/routing_seeds.tex} |
| 109 | 112 | |
| 110 | 113 | \subsection{Token loss versus task success}\label{sec:results-reasoning} |
| 111 | −Exact match of free greedy generation moves with the loss on dev-iid (Table~\ref{tab:seedmatrix}: $+1.8$ points | |
| 112 | −for the sparse editor at budget 2, $+2.3$ for global recurrence at budget 8, seed SD $\le 0.5$) but not on the | |
| 113 | −held-out regimes; per-family transitions are reported in Appendix~\ref{app:results}. No adapter turns the | |
| 114 | −held-out compose family from near zero (2--3\,\%) into anything else. | |
| 114 | +Exact match of free greedy generation moves with the loss on dev-iid but by less than the pre-registered | |
| 115 | +minimum effect of three points (Table~\ref{tab:stats}): the sparse editor gains $+1.9$ points at budget 2 | |
| 116 | +(95\,\% $t$-interval over five seeds $[+1.6,+2.2]$; every per-seed paired item bootstrap excludes zero), global | |
| 117 | +recurrence gains $+1.9$ at budget 2 and $+2.3$ at budget 8, and the paired difference between the two systems | |
| 118 | +at budget 2 is $+0.1$ points $[-0.5,+0.7]$---a null---while at budget 1 global recurrence is ahead by $0.6$ | |
| 119 | +points $[0.3,0.9]$. Transitions are two-sided: at budget 2 the sparse editor turns \vtwoprismetransplus{} | |
| 120 | +items per thousand from wrong to right and \vtwoprismetransminus{} from right to wrong | |
| 121 | +(Table~\ref{tab:emfamilies}); gains concentrate in \textsf{fsm} and \textsf{bind}, \textsf{excl} does not move. | |
| 122 | +No adapter changes the held-out regimes by more than a point, and the compose family stays at 2--3\,\%. | |
| 123 | +\input{tables/stats.tex} | |
| 115 | 124 | |
| 116 | 125 | \subsection{Latency and memory}\label{sec:results-latency} |
| 117 | 126 | Table~\ref{tab:latency} gives measured batch-1 and batch-8 decode latencies for the tiny model on the |
modified
paper/tables/numbers.tex
+6 −6
@@ -57,12 +57,12 @@ | ||
| 57 | 57 | \newcommand{\routinguniformbeight}{+0.6} |
| 58 | 58 | \newcommand{\routinguniformbone}{-0.8} |
| 59 | 59 | \newcommand{\routinguniformbtwo}{-0.7} |
| 60 | −\newcommand{\vtwobestfixedrel}{-4.0} | |
| 60 | +\newcommand{\vtwobestfixedrel}{-4.2} | |
| 61 | 61 | \newcommand{\vtwobzeroloss}{0.4621} |
| 62 | −\newcommand{\vtwoctrlbetter}{2} | |
| 63 | −\newcommand{\vtwoctrlrel}{+0.5} | |
| 64 | −\newcommand{\vtwoctrlrelsd}{1.1} | |
| 65 | −\newcommand{\vtwoctrlseeds}{4} | |
| 62 | +\newcommand{\vtwoctrlbetter}{3} | |
| 63 | +\newcommand{\vtwoctrlrel}{+0.3} | |
| 64 | +\newcommand{\vtwoctrlrelsd}{1.0} | |
| 65 | +\newcommand{\vtwoctrlseeds}{5} | |
| 66 | 66 | \newcommand{\vtwodenseembeight}{n/a} |
| 67 | 67 | \newcommand{\vtwodenseembtwo}{n/a} |
| 68 | 68 | \newcommand{\vtwodenseembzero}{n/a} |
@@ -81,7 +81,7 @@ | ||
| 81 | 81 | \newcommand{\vtwogrseeds}{5} |
| 82 | 82 | \newcommand{\vtwogrtransminus}{39} |
| 83 | 83 | \newcommand{\vtwogrtransplus}{57} |
| 84 | −\newcommand{\vtwooraclerel}{-15.0} | |
| 84 | +\newcommand{\vtwooraclerel}{-15.1} | |
| 85 | 85 | \newcommand{\vtwoprismeembeight}{39.2} |
| 86 | 86 | \newcommand{\vtwoprismeembtwo}{39.6} |
| 87 | 87 | \newcommand{\vtwoprismeembzero}{37.7} |
modified
paper/tables/routing_seeds.tex
+1 −0
@@ -7,6 +7,7 @@ opportunity for each controller.} | ||
| 7 | 7 | \label{tab:routingseeds} |
| 8 | 8 | \begin{tabular}{lrlrrrrrr}\toprule |
| 9 | 9 | seed & budget 0 & best fixed & entropy & norm & controller (edits) & oracle b=8 (edits) & sign acc. & captured\\\midrule |
| 10 | +1 & 0.4966 & 0.4738 (random forced b=4) & 0.4780 & 0.4774 & 0.4950 (0.18) & 0.4198 (2.16) & 0.622 & +0.415\\ | |
| 10 | 11 | 2 & 0.4966 & 0.4754 (random forced b=4) & 0.4799 & 0.4794 & 0.4965 (0.05) & 0.4114 (1.90) & 0.413 & +0.333\\ |
| 11 | 12 | 3 & 0.4966 & 0.4775 (uniform b=8) & 0.4825 & 0.4814 & 0.5074 (4.32) & 0.4242 (1.84) & 0.504 & +0.305\\ |
| 12 | 13 | 4 & 0.4966 & 0.4762 (uniform b=8) & 0.4795 & 0.4790 & 0.4974 (0.17) & 0.4251 (2.19) & 0.633 & +0.521\\ |
added
paper/tables/stats.tex
+17 −0
@@ -0,0 +1,17 @@ | ||
| 1 | +\begin{table}[t]\centering\small | |
| 2 | +\caption{Pre-registered uncertainty analysis of dev-iid exact match (percentage points). ``t-CI'' is the 95\,\% | |
| 3 | +$t$-interval over independent adapter seeds of the per-seed paired difference; ``item CI range'' spans the | |
| 4 | +smallest lower and largest upper bound of the per-seed paired item bootstraps (10,000 resamples, 1,000 items).} | |
| 5 | +\label{tab:stats} | |
| 6 | +\begin{tabular}{lrrll}\toprule | |
| 7 | +Comparison & seeds & mean & t-CI over seeds & item CI range\\\midrule | |
| 8 | +prisme b1 vs b0 & 5 & +1.58 & [+1.21, +1.95] & [+0.30, +3.30]\\ | |
| 9 | +prisme b2 vs b0 & 5 & +1.92 & [+1.60, +2.24] & [+0.10, +3.90]\\ | |
| 10 | +prisme b8 vs b0 & 5 & +1.50 & [+0.94, +2.06] & [-1.10, +4.50]\\ | |
| 11 | +gr b1 vs b0 & 5 & +2.14 & [+1.76, +2.52] & [+0.20, +4.10]\\ | |
| 12 | +gr b2 vs b0 & 5 & +1.86 & [+1.37, +2.35] & [-0.30, +4.50]\\ | |
| 13 | +gr b8 vs b0 & 5 & +2.34 & [+0.97, +3.71] & [-1.40, +6.20]\\ | |
| 14 | +prisme minus gr b1 & 5 & -0.56 & [-0.85, -0.27] & [-2.20, +0.90]\\ | |
| 15 | +prisme minus gr b2 & 5 & +0.06 & [-0.53, +0.65] & [-2.20, +2.00]\\ | |
| 16 | +prisme minus gr b8 & 5 & -0.84 & [-2.43, +0.75] & [-4.40, +2.50]\\ | |
| 17 | +\bottomrule\end{tabular}\end{table} | |
modified
results/analyzed/routing_seeds_v2.json
+16 −0
@@ -1,4 +1,20 @@ | ||
| 1 | 1 | [ |
| 2 | + { | |
| 3 | + "seed": "1", | |
| 4 | + "b0": 0.4965549189338985, | |
| 5 | + "best_fixed": 0.4737940016007751, | |
| 6 | + "best_fixed_name": "random forced b=4", | |
| 7 | + "entropy": 0.47797408758425247, | |
| 8 | + "norm": 0.4774494416747904, | |
| 9 | + "ctrl": 0.4950156743532738, | |
| 10 | + "ctrl_edits": 0.18027509511267192, | |
| 11 | + "ctrl_lam": 0.3, | |
| 12 | + "ctrl_kap": 0.5, | |
| 13 | + "oracle8": 0.4197931946875673, | |
| 14 | + "oracle8_edits": 2.1623277182235836, | |
| 15 | + "sign_acc": 0.6217491454896715, | |
| 16 | + "captured": 0.41516637065089457 | |
| 17 | + }, | |
| 2 | 18 | { |
| 3 | 19 | "seed": "2", |
| 4 | 20 | "b0": 0.49655490497905047, |
added
results/analyzed/statistics_v2.json
+506 −0
@@ -0,0 +1,506 @@ | ||
| 1 | +{ | |
| 2 | + "prisme_b1_vs_b0": { | |
| 3 | + "per_seed": [ | |
| 4 | + { | |
| 5 | + "diff": 0.021, | |
| 6 | + "ci_low": 0.01, | |
| 7 | + "ci_high": 0.033, | |
| 8 | + "n": 1000, | |
| 9 | + "p_two_sided": 0.0, | |
| 10 | + "run_id": "p4v2_prisme_seed01_20261030001749" | |
| 11 | + }, | |
| 12 | + { | |
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| 15 | + "ci_high": 0.025, | |
| 16 | + "n": 1000, | |
| 17 | + "p_two_sided": 0.0154, | |
| 18 | + "run_id": "p4v2_prisme_seed02_20261030001749" | |
| 19 | + }, | |
| 20 | + { | |
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| 24 | + "n": 1000, | |
| 25 | + "p_two_sided": 0.0182, | |
| 26 | + "run_id": "p4v2_prisme_seed03_20261030001749" | |
| 27 | + }, | |
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| 33 | + "p_two_sided": 0.0104, | |
| 34 | + "run_id": "p4v2_prisme_seed04_20261030001749" | |
| 35 | + }, | |
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| 195 | + "run_id": "p4v2_gr_seed05_20261030001839" | |
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| 206 | + "gr_b2_vs_b0": { | |
| 207 | + "per_seed": [ | |
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| 246 | + "run_id": "p4v2_gr_seed05_20261030001839" | |
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| 249 | + "seeds": { | |
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| 251 | + "sd": 0.00391152144312159, | |
| 252 | + "ci_low": 0.013743204645873891, | |
| 253 | + "ci_high": 0.023456795354126113, | |
| 254 | + "n": 5 | |
| 255 | + } | |
| 256 | + }, | |
| 257 | + "gr_b8_vs_b0": { | |
| 258 | + "per_seed": [ | |
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| 265 | + "run_id": "p4v2_gr_seed01_20261030001749" | |
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| 288 | + "p_two_sided": 0.0014, | |
| 289 | + "run_id": "p4v2_gr_seed04_20261030001749" | |
| 290 | + }, | |
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| 295 | + "n": 1000, | |
| 296 | + "p_two_sided": 0.5004, | |
| 297 | + "run_id": "p4v2_gr_seed05_20261030001839" | |
| 298 | + } | |
| 299 | + ], | |
| 300 | + "seeds": { | |
| 301 | + "mean": 0.023400000000000004, | |
| 302 | + "sd": 0.011058933040759403, | |
| 303 | + "ci_low": 0.009668520984742975, | |
| 304 | + "ci_high": 0.037131479015257034, | |
| 305 | + "n": 5 | |
| 306 | + } | |
| 307 | + }, | |
| 308 | + "prisme_minus_gr_b1": { | |
| 309 | + "per_seed": [ | |
| 310 | + { | |
| 311 | + "diff": -0.004, | |
| 312 | + "ci_low": -0.017, | |
| 313 | + "ci_high": 0.009, | |
| 314 | + "n": 1000, | |
| 315 | + "p_two_sided": 0.6038, | |
| 316 | + "run_ids": [ | |
| 317 | + "p4v2_prisme_seed01_20261030001749", | |
| 318 | + "p4v2_gr_seed01_20261030001749" | |
| 319 | + ] | |
| 320 | + }, | |
| 321 | + { | |
| 322 | + "diff": -0.004, | |
| 323 | + "ci_low": -0.017, | |
| 324 | + "ci_high": 0.009, | |
| 325 | + "n": 1000, | |
| 326 | + "p_two_sided": 0.603, | |
| 327 | + "run_ids": [ | |
| 328 | + "p4v2_prisme_seed02_20261030001749", | |
| 329 | + "p4v2_gr_seed02_20261030001749" | |
| 330 | + ] | |
| 331 | + }, | |
| 332 | + { | |
| 333 | + "diff": -0.007, | |
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| \ No newline at end of file | ||
added
results/raw/routing_v1rank.json
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| \ No newline at end of file | ||
added
results/raw/routing_v2s1.json
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@@ -0,0 +1,290 @@ | ||
| 1 | +{ | |
| 2 | + "config": "configs/experiments/routing_v2s1.yaml", | |
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| 289 | + ] | |
| 290 | +} | |
| \ No newline at end of file | ||
added
scripts/statistics.py
+59 −0
@@ -0,0 +1,59 @@ | ||
| 1 | +#!/usr/bin/env python | |
| 2 | +"""Pre-registered uncertainty analysis: paired item-level bootstrap (10,000 resamples) of exact-match differences | |
| 3 | +within each seed, and t-intervals over seeds. Writes results/analyzed/statistics_v2.json and paper/tables/stats.tex.""" | |
| 4 | +import glob, json, sys | |
| 5 | +from pathlib import Path | |
| 6 | +import numpy as np | |
| 7 | +sys.path.insert(0, ".") | |
| 8 | +from evaluation.statistical_analysis import paired_bootstrap, seed_interval | |
| 9 | + | |
| 10 | +def load(pre): | |
| 11 | + out = [] | |
| 12 | + for run in sorted(glob.glob(f"experiments/runs/{pre}_seed*")): | |
| 13 | + if json.load(open(Path(run) / "manifest.json")).get("state") != "completed": | |
| 14 | + continue | |
| 15 | + recs = {} | |
| 16 | + for b in (0, 1, 2, 8): | |
| 17 | + p = Path(run) / f"em_dev_iid_b{b}.json" | |
| 18 | + if p.exists(): | |
| 19 | + recs[b] = {r["uid"]: r["correct"] for r in json.load(open(p))} | |
| 20 | + out.append((Path(run).name, recs)) | |
| 21 | + return out | |
| 22 | + | |
| 23 | +res = {} | |
| 24 | +systems = {"prisme": load("p4v2_prisme"), "gr": load("p4v2_gr"), "dense": load("p4v2_dense")} | |
| 25 | +for name, runs in systems.items(): | |
| 26 | + for b in (1, 2, 8): | |
| 27 | + diffs, boots = [], [] | |
| 28 | + for rid, recs in runs: | |
| 29 | + if b in recs and 0 in recs: | |
| 30 | + common = sorted(set(recs[0]) & set(recs[b])) | |
| 31 | + a = np.array([recs[b][u] for u in common]); c = np.array([recs[0][u] for u in common]) | |
| 32 | + bs = paired_bootstrap(a, c); bs["run_id"] = rid; boots.append(bs); diffs.append(bs["diff"]) | |
| 33 | + if diffs: | |
| 34 | + res[f"{name}_b{b}_vs_b0"] = {"per_seed": boots, "seeds": seed_interval(diffs)} | |
| 35 | +# PRISME vs GR at the same budget (paired by item, per seed index) | |
| 36 | +for b in (1, 2, 8): | |
| 37 | + diffs, boots = [], [] | |
| 38 | + for (rp, rec_p), (rg, rec_g) in zip(systems["prisme"], systems["gr"]): | |
| 39 | + if b in rec_p and b in rec_g: | |
| 40 | + common = sorted(set(rec_p[b]) & set(rec_g[b])) | |
| 41 | + a = np.array([rec_p[b][u] for u in common]); c = np.array([rec_g[b][u] for u in common]) | |
| 42 | + bs = paired_bootstrap(a, c); bs["run_ids"] = [rp, rg]; boots.append(bs); diffs.append(bs["diff"]) | |
| 43 | + if diffs: | |
| 44 | + res[f"prisme_minus_gr_b{b}"] = {"per_seed": boots, "seeds": seed_interval(diffs)} | |
| 45 | +Path("results/analyzed").mkdir(exist_ok=True, parents=True) | |
| 46 | +Path("results/analyzed/statistics_v2.json").write_text(json.dumps(res, indent=1)) | |
| 47 | +rows = [] | |
| 48 | +for k, v in res.items(): | |
| 49 | + s = v["seeds"]; lo = min(b["ci_low"] for b in v["per_seed"]); hi = max(b["ci_high"] for b in v["per_seed"]) | |
| 50 | + rows.append(f"{k.replace('_', ' ')} & {s['n']} & {100*s['mean']:+.2f} & [{100*s['ci_low']:+.2f}, {100*s['ci_high']:+.2f}] & [{100*lo:+.2f}, {100*hi:+.2f}]\\\\") | |
| 51 | + print(k, "seeds", s["n"], f"mean {100*s['mean']:+.2f} pp, t-CI [{100*s['ci_low']:+.2f}, {100*s['ci_high']:+.2f}]") | |
| 52 | +Path("paper/tables/stats.tex").write_text(r"""\begin{table}[t]\centering\small | |
| 53 | +\caption{Pre-registered uncertainty analysis of dev-iid exact match (percentage points). ``t-CI'' is the 95\,\% | |
| 54 | +$t$-interval over independent adapter seeds of the per-seed paired difference; ``item CI range'' spans the | |
| 55 | +smallest lower and largest upper bound of the per-seed paired item bootstraps (10,000 resamples, 1,000 items).} | |
| 56 | +\label{tab:stats} | |
| 57 | +\begin{tabular}{lrrll}\toprule | |
| 58 | +Comparison & seeds & mean & t-CI over seeds & item CI range\\\midrule | |
| 59 | +""" + "\n".join(rows) + "\n" + r"\bottomrule\end{tabular}\end{table}" + "\n") | |
| 60 | ||