Manuscript revision and pending experiment work, snapshot before restructuring
Clarity pass over the main text (36-item audit), Discussion rewrite and cut, acknowledgements, Souly et al. as ref 62, lettered SI panels, model section moved under Results; plus the untracked curriculum/society/compose/smol configs, runners, figures, stats and tests that the SI already cites. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
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results/llm_curriculum_v5_stop3/README.md
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results/llm_curriculum_v5_stop3/README.md
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# llm_curriculum_v5_stop3 — forced stop at generation 3 (control for the declinable merge)
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Config `configs/llm/curriculum_v5_stop3.yaml`: the v5 `society` arm (three lineages, six real-dataset
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families in a Latin square, Qwen2.5-1.5B base, rank-16 adapters continued from the parent) with
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recombination switched off from generation 3 (`merge_until: 3`, no veto). Generations 0–2 merge
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obligately; 3–5 never. Pre-registered in `tasks/prereg-llm-society-v4.md` §8h before running.
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Seed 1 local (batch 24 / train batch 2); seeds 2–3 on CX3 via `hpc/llm_curriculum_controls.pbs`
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(batch 48 / train batch 4), as in the v5 campaign. Layout: `results.parquet` (seed 1), `s2/`, `s3/`.
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Why: in the seed-1 veto run lineages declined 1/3 of merges at generations 0–2 and 3/3 at 3–5, so
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this is the fixed schedule the declinable merge's *timing* must be separated from.
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## Result (best lineage, all six families, generation 5; `figures/stats_llm_curriculum.py`)
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| arm | s1 | s2 | s3 | mean |
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|---|---|---|---|---|
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| forced stop at 3 (this run) | 0.792 | 0.794 | 0.792 | 0.793 |
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| declinable merge (veto) | 0.783 | 0.789 | 0.803 | 0.792 |
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| never merge (isolated) | 0.814 | 0.783 | 0.792 | 0.796 |
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| always merge (society) | 0.211 | 0.247 | 0.350 | 0.269 |
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| contrast | s1 | s2 | s3 | mean ± 95% CI |
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|---|---|---|---|---|
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| veto − stop3 | −0.008 | −0.006 | +0.011 | −0.001 ± 0.012 |
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| stop3 − isolated | −0.022 | +0.011 | 0.000 | −0.004 ± 0.019 |
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| stop3 − society | +0.581 | +0.547 | +0.442 | +0.523 ± 0.082 |
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Pre-registered reading (§8h, first branch): the forced stop matches the veto within ±0.03 in every
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seed, so the declinable merge's final accuracy is explained by *when* it stopped merging. What the
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veto adds is that it found that schedule by measurement rather than by having it set in advance;
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the claim that per-decision evaluation adds value beyond timing is not supported here. Both
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non-obligate schedules avoid the collapse of obligate merging (+0.52 over `society`).
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Falsifier status: the paper's caveat "the control separating the modifier's timing from a fixed
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early stop was not run" is removed; the modifier claim is reduced accordingly.
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48
results/llm_curriculum_v5_stop3/manifest.json
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results/llm_curriculum_v5_stop3/manifest.json
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{
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"experiment": "llm_curriculum_v5_stop3",
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"master_seed": 1,
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"git_commit": "e4804adabcdce6d928c5e6b1e85429b2a6acf2fe",
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"python": "3.14.7",
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"libraries": {
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"numpy": "2.5.0",
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"scipy": "1.18.0",
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"pandas": "3.0.3",
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"pyarrow": "24.0.0",
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"torch": "2.12.1",
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"transformers": "5.16.1",
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"peft": "0.20.0"
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},
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"rows": 205,
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"results_sha256": "a2096209e2203a6e6295a6deca1bc6a45b5894e6a2c74e267444a0cd7c97174d",
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"layer": "2",
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"tier": "llm",
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"base_model": "Qwen/Qwen2.5-1.5B",
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"hard": false,
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"curriculum": {
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"families": [
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"mnli",
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"arc",
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"hellaswag",
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"squad",
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"boolq",
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"winogrande"
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],
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"lineages": 3,
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"generations": 6,
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"arms": [
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"society"
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],
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"baselines": [],
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"n_new": 300,
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"n_replay": 150,
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"operator": "linear",
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"ancestor_depth": null,
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"lora": {
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"r": 16,
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"alpha": 32
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},
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"allow_veto": false,
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"merge_until": 3,
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"orders": null
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}
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}
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results/llm_curriculum_v5_stop3/partial_society_s1.parquet
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results/llm_curriculum_v5_stop3/partial_society_s1.parquet
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results/llm_curriculum_v5_stop3/resolved_config.yaml
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results/llm_curriculum_v5_stop3/resolved_config.yaml
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experiment: llm_curriculum_v5_stop3
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seed: 1
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n_replicates: 1
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source_config:
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experiment: llm_curriculum_v5_stop3
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kind: llm_curriculum
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base_model: Qwen/Qwen2.5-1.5B
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seed: 1
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families:
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- mnli
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- arc
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- hellaswag
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- squad
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- boolq
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- winogrande
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lineages: 3
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generations: 6
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arms:
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- society
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baselines: []
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allow_veto: false
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merge_until: 3
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n_new: 300
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n_replay: 150
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n_test: 60
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n_val: 20
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epochs: 3
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lr: 0.0001
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operator: linear
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merge_weights:
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- - 0.5
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- 0.5
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- - 0.3
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- 0.7
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- - 0.7
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- 0.3
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max_new_tokens: 48
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batch_size: 24
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train_batch_size: 2
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train_max_len: 512
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lora:
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r: 16
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alpha: 32
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output:
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dir: results/llm_curriculum_v5_stop3
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n_replicates: 1
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48
results/llm_curriculum_v5_stop3/s2/manifest.json
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results/llm_curriculum_v5_stop3/s2/manifest.json
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{
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"experiment": "llm_curriculum_v5_stop3",
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"master_seed": 2,
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"git_commit": null,
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"python": "3.11.7",
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"libraries": {
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"numpy": "2.4.6",
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"scipy": "1.17.1",
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"pandas": "3.0.3",
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"pyarrow": "24.0.0",
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"torch": "2.12.1",
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"transformers": "5.16.1",
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"peft": "0.20.0"
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},
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"rows": 205,
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"results_sha256": "cdcd68e8f66fcc48974633eeb31e88fafe318b7f821145393291d2402607dd18",
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"layer": "2",
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"tier": "llm",
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"base_model": "Qwen/Qwen2.5-1.5B",
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"hard": false,
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"curriculum": {
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"families": [
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"mnli",
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"arc",
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"hellaswag",
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"squad",
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"boolq",
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"winogrande"
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],
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"lineages": 3,
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"generations": 6,
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"arms": [
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"society"
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],
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"baselines": [],
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"n_new": 300,
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"n_replay": 150,
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"operator": "linear",
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"ancestor_depth": null,
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"lora": {
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"r": 16,
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"alpha": 32
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},
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"allow_veto": false,
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"merge_until": 3,
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"orders": null
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}
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}
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results/llm_curriculum_v5_stop3/s2/partial_society_s2.parquet
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results/llm_curriculum_v5_stop3/s2/partial_society_s2.parquet
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results/llm_curriculum_v5_stop3/s2/resolved_config.yaml
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results/llm_curriculum_v5_stop3/s2/resolved_config.yaml
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experiment: llm_curriculum_v5_stop3
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seed: 2
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n_replicates: 1
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source_config:
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experiment: llm_curriculum_v5_stop3
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kind: llm_curriculum
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base_model: Qwen/Qwen2.5-1.5B
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seed: 2
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families:
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- mnli
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- arc
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- hellaswag
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- squad
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- boolq
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- winogrande
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lineages: 3
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generations: 6
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arms:
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- society
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baselines: []
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allow_veto: false
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merge_until: 3
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n_new: 300
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n_replay: 150
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n_test: 60
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n_val: 20
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epochs: 3
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lr: 0.0001
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operator: linear
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merge_weights:
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- - 0.5
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- 0.5
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- - 0.3
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- 0.7
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- - 0.7
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- 0.3
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max_new_tokens: 48
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batch_size: 48
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train_batch_size: 4
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train_max_len: 512
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lora:
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r: 16
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alpha: 32
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output:
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dir: results/llm_curriculum_v5_stop3/s2
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n_replicates: 1
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48
results/llm_curriculum_v5_stop3/s3/manifest.json
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results/llm_curriculum_v5_stop3/s3/manifest.json
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{
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"experiment": "llm_curriculum_v5_stop3",
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"master_seed": 3,
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"git_commit": null,
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"python": "3.11.7",
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"libraries": {
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"numpy": "2.4.6",
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"scipy": "1.17.1",
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"pandas": "3.0.3",
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"pyarrow": "24.0.0",
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"torch": "2.12.1",
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"transformers": "5.16.1",
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"peft": "0.20.0"
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},
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"rows": 205,
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"results_sha256": "1a924dad6710b9258dffb70e4496b0c4480e36ab8c7f76dae1a1c669e023b382",
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"layer": "2",
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"tier": "llm",
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"base_model": "Qwen/Qwen2.5-1.5B",
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"hard": false,
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"curriculum": {
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"families": [
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"mnli",
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"arc",
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"hellaswag",
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"squad",
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"boolq",
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"winogrande"
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],
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"lineages": 3,
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"generations": 6,
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"arms": [
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"society"
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],
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"baselines": [],
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"n_new": 300,
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"n_replay": 150,
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"operator": "linear",
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"ancestor_depth": null,
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"lora": {
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"r": 16,
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"alpha": 32
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},
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"allow_veto": false,
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"merge_until": 3,
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"orders": null
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}
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}
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results/llm_curriculum_v5_stop3/s3/partial_society_s3.parquet
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results/llm_curriculum_v5_stop3/s3/partial_society_s3.parquet
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results/llm_curriculum_v5_stop3/s3/resolved_config.yaml
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results/llm_curriculum_v5_stop3/s3/resolved_config.yaml
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experiment: llm_curriculum_v5_stop3
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seed: 3
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n_replicates: 1
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source_config:
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experiment: llm_curriculum_v5_stop3
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kind: llm_curriculum
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base_model: Qwen/Qwen2.5-1.5B
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seed: 3
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families:
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- mnli
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- arc
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- hellaswag
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- squad
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- boolq
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- winogrande
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lineages: 3
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generations: 6
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arms:
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- society
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baselines: []
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allow_veto: false
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merge_until: 3
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n_new: 300
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n_replay: 150
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n_test: 60
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n_val: 20
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epochs: 3
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lr: 0.0001
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operator: linear
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merge_weights:
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- - 0.5
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- 0.5
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- - 0.3
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- 0.7
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- - 0.7
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- 0.3
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max_new_tokens: 48
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batch_size: 48
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train_batch_size: 4
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train_max_len: 512
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lora:
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r: 16
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alpha: 32
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output:
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dir: results/llm_curriculum_v5_stop3/s3
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n_replicates: 1
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