Giorgio Gilestro
aca7b394a3
configs/neural/{N0,N1,N2,N5}.yaml -> {bridge,collapse,grounding,architectures}.yaml,
results dirs likewise. Updated experiment/output.dir fields, comments/docstrings, and
docs; regenerated the four result manifests (now carrying the real git commit). No
functional path resolution referenced the codes (the Makefile globs configs/neural/*.yaml
and tests use inline configs), so nothing breaks. 92 tests green.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
50 lines
1.2 KiB
YAML
50 lines
1.2 KiB
YAML
experiment: collapse_in_weights
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kind: gen_lineage
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seed: 20260704
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n_replicates: 5
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# (maps to Layer-1 E1 / blueprint C1): does model collapse appear in REAL
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# trained weights under dry recursive self-training, and does a little grounding arrest it?
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# An autoregressive RNN is retrained each generation on n samples drawn from the previous
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# generation's RNN (drift), optionally mixed with m verifier-grounded samples. Expect: the
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# dry arm (g=0) loses diversity (H falls) and forgets the tail (forward-KL to truth rises,
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# tail_mass shrinks); grounded arms hold. Falsifier: dry inheritance does not degrade in
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# real weights -> the neural collapse claim is unsupported at this scale.
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generations: 25
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synthetic:
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K: 256
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R: 1
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tail: zipf
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zipf_s: 1.3
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tail_frac: 0.5
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tail_threshold: 1.0e-3
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init: truth
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style_len: 3
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style_vocab: 5
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id_base: 2
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model:
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kind: rnn
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hidden: 128
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embed: 24
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epochs: 25
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lr: 2.0e-3
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batch_size: 256
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n_eval: 12000
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dynamics:
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n: 200
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grounding: {m: 0, policy: proportional} # m overwritten per g by the sweep
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remint: {enabled: false, period: null, H_gate: null}
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metrics:
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kl_floor: 1.0e-9
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support_eps: 1.0e-9
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sweep:
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- param: g
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values: [0.0, 0.02, 0.05, 0.1]
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output:
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dir: results/collapse
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