Giorgio Gilestro
84124de143
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
55 lines
1.4 KiB
YAML
55 lines
1.4 KiB
YAML
# The composition campaign, seed 1 (prereg v3, amended after the generation-0 sweep of 2026-09-07).
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#
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# Arms. The gen-0 sweep found that the merge *weighting* dominates the operator: the a-priori 0.5/0.5
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# blend fails under both operators (surplus -0.020 cat, -0.093 linear) while a selected weight passes
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# (+0.080 linear at 0.2/0.8, +0.027 cat at 0.3/0.7). Weights are therefore chosen each generation on a
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# disjoint validation split (E10, directed recombination) in every arm, and the operator is an
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# explicit per-arm setting:
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# dry — linear operator, no grounding [H2, H3, H5: does composition survive drift?]
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# grounded — linear operator, g = 0.10 [H4: does immigration arrest it?]
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# dry_cat — concatenation operator, no grounding [H6, revised: does the operator ordering hold
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# across generations, or only at gen 0?]
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experiment: llm_compose
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kind: llm_compose
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base_model: Qwen/Qwen2.5-1.5B
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seed: 1
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generations: 6
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arms:
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- dry
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- grounded
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- dry_cat
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g: 0.1
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n_hard: 150
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n_gsm8k: 150
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n_mbpp: 100
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n_probe: 60
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k_inherit: 300
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epochs: 3
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conf_gate: 0.85
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spec_train: 1200
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spec_epochs: 3
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max_new_tokens: 320
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batch_size: 16
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score_batch_size: 4
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train_batch_size: 2
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train_max_len: 448
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resume: true
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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_compose/s1
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arm_ops:
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dry: linear
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grounded: linear
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dry_cat: cat
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n_hard_val: 60
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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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- - 0.2
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- 0.8
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- - 0.1
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- 0.9
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