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  "params": 24614453,
  "role": "PNSR typed learned state, seed 1 (additive write, clamp tau=16)",
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  "seed": 1,
  "source_run_directory": "PNSR_K4_fin",
  "state_dict_tensor_total": 27760181,
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   "batch": 160,
   "lr": 0.0004,
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   "run": "PNSR_K4_v2",
   "seed": 1,
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 },
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   "vocab": 8192,
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  "params": 24614453,
  "role": "PNSR typed learned state, seed 2",
  "run": "PNSR_K4_s2",
  "seed": 2,
  "source_run_directory": "PNSR_K4_s2",
  "state_dict_tensor_total": 27760181,
  "train_args": {
   "batch": 160,
   "gate_bias": 0.0,
   "hold_frac": null,
   "lr": 0.0004,
   "model": "pnsr",
   "resume_from": null,
   "run": "PNSR_K4_s2",
   "seed": 2,
   "state_tau": 16.0,
   "update_rule": "additive_clamp",
   "updates": 6000,
   "w_enum": 2.0,
   "w_other": 1.0
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  "updates": 6000
 },
 "PNSR_K4_s3": {
  "admission_note": "the run's own final checkpoint",
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  "admitted_from_run": "PNSR_K4_s3",
  "batch": 160,
  "cfg": {
   "K": 4,
   "T_ev": 48,
   "d": 384,
   "enc_layers": 7,
   "heads": 8,
   "n_workspace": 4,
   "state_tau": 16.0,
   "update_rule": "additive_clamp",
   "vocab": 8192,
   "write_mode": "independent",
   "write_temp": 1.0
  },
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  "lr": 0.0004,
  "param_count_note": "params = distinct trainable parameters (the paper's matched-budget figure). The event encoder and record encoder share one tied 8192x384 token embedding, so state_dict lists it twice; state_dict_tensor_total is that raw sum and is ~3.15M larger for the 25M models.",
  "params": 24614453,
  "role": "PNSR typed learned state, seed 3",
  "run": "PNSR_K4_s3",
  "seed": 3,
  "source_run_directory": "PNSR_K4_s3",
  "state_dict_tensor_total": 27760181,
  "train_args": {
   "batch": 160,
   "gate_bias": 0.0,
   "hold_frac": null,
   "lr": 0.0004,
   "model": "pnsr",
   "resume_from": null,
   "run": "PNSR_K4_s3",
   "seed": 3,
   "state_tau": 16.0,
   "update_rule": "additive_clamp",
   "updates": 6000,
   "w_enum": 2.0,
   "w_other": 1.0
  },
  "train_corpus": "train",
  "updates": 6000
 },
 "PNSR_ON_E3": {
  "admission_note": "the run's own final checkpoint",
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  "admitted_from_run": "PNSR_ON_E3",
  "batch": 96,
  "cfg": {
   "K": 4,
   "T_ev": 48,
   "d": 384,
   "enc_layers": 7,
   "heads": 8,
   "n_workspace": 4,
   "state_tau": 16.0,
   "update_rule": "additive_clamp",
   "vocab": 8192,
   "write_mode": "independent",
   "write_temp": 1.0
  },
  "group": "corrected_corpus",
  "kind": "pnsr",
  "lr": 0.0004,
  "param_count_note": "params = distinct trainable parameters (the paper's matched-budget figure). The event encoder and record encoder share one tied 8192x384 token embedding, so state_dict lists it twice; state_dict_tensor_total is that raw sum and is ~3.15M larger for the 25M models.",
  "params": 24614453,
  "role": "E1 architecture retrained from scratch on the corrected corpus",
  "run": "PNSR_ON_E3",
  "seed": 1,
  "source_run_directory": "PNSR_ON_E3",
  "state_dict_tensor_total": 27760181,
  "train_args": {
   "batch": 96,
   "gate_bias": 0.0,
   "hold_frac": null,
   "lr": 0.0004,
   "model": "pnsr",
   "resume_from": null,
   "run": "PNSR_ON_E3",
   "seed": 1,
   "shards_split": "e3_train",
   "state_tau": 16.0,
   "update_rule": "additive_clamp",
   "updates": 6000,
   "w_enum": 2.0,
   "w_other": 1.0
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  "train_corpus": "e3_train",
  "updates": 6000
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 "RMT_s1": {
  "admission_note": "the run's own final checkpoint",
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  "admitted_from_run": "RMT_s1",
  "batch": 160,
  "cfg": {
   "T_ev": 48,
   "d": 384,
   "heads": 8,
   "layers": 10,
   "n_mem": 32,
   "vocab": 8192
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  "group": "experiment1",
  "kind": "rmt",
  "lr": 0.0003,
  "param_count_note": "params = distinct trainable parameters (the paper's matched-budget figure). The event encoder and record encoder share one tied 8192x384 token embedding, so state_dict lists it twice; state_dict_tensor_total is that raw sum and is ~3.15M larger for the 25M models.",
  "params": 23945525,
  "role": "memory-token recurrent baseline (RMT-style), seed 1",
  "run": "RMT_s1",
  "seed": 1,
  "source_run_directory": "RMT_s1",
  "state_dict_tensor_total": 27091253,
  "train_args": {
   "batch": 160,
   "gate_bias": 0.0,
   "hold_frac": null,
   "lr": 0.0003,
   "model": "rmt",
   "resume_from": null,
   "run": "RMT_s1",
   "seed": 1,
   "state_tau": 16.0,
   "update_rule": "additive_clamp",
   "updates": 6000,
   "w_enum": 2.0,
   "w_other": 1.0
  },
  "train_corpus": "train",
  "updates": 6000
 },
 "TX768_fin": {
  "admission_note": "amendment A7: v2/v3 invalid (v3 was frozen mid-run by the A3 skip-guard, AUDIT 2); v4 retrained with the guard removed, lr 1.5e-4, exposure-matched; best.pt (update 18250) is the admitted checkpoint",
  "admitted_checkpoint": "best.pt",
  "admitted_from_run": "TX768_v4",
  "batch": 384,
  "cfg": {
   "d": 384,
   "heads": 8,
   "layers": 10,
   "vocab": 8192,
   "window": 768
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  "group": "experiment1",
  "kind": "tx768",
  "lr": 0.00015,
  "param_count_note": "params = distinct trainable parameters (the paper's matched-budget figure). The event encoder and record encoder share one tied 8192x384 token embedding, so state_dict lists it twice; state_dict_tensor_total is that raw sum and is ~3.15M larger for the 25M models.",
  "params": 23892917,
  "role": "transcript-window baseline, 768 tokens (~40 events)",
  "run": "TX768_fin",
  "seed": 1,
  "source_run_directory": "TX768_fin",
  "state_dict_tensor_total": 27038645,
  "train_args": {
   "batch": 384,
   "hold_frac": 0.0,
   "lr": 0.00015,
   "model": "tx768",
   "resume_from": null,
   "run": "TX768_v4",
   "seed": 1,
   "updates": 18850,
   "w_enum": 2.0,
   "w_other": 1.0
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  "train_corpus": "train",
  "updates": 18850
 },
 "TXE_ON_E3": {
  "admission_note": "the run's own final checkpoint",
  "admitted_checkpoint": "final.pt",
  "admitted_from_run": "TXE_ON_E3",
  "batch": 384,
  "cfg": {
   "d": 384,
   "heads": 8,
   "layers": 10,
   "vocab": 8192,
   "window": 64
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  "group": "corrected_corpus",
  "kind": "txe",
  "lr": 0.0003,
  "param_count_note": "params = distinct trainable parameters (the paper's matched-budget figure). The event encoder and record encoder share one tied 8192x384 token embedding, so state_dict lists it twice; state_dict_tensor_total is that raw sum and is ~3.15M larger for the 25M models.",
  "params": 23622581,
  "role": "memory-free control on the corrected corpus (Experiment 2 comparator)",
  "run": "TXE_ON_E3",
  "seed": 1,
  "source_run_directory": "TXE_ON_E3",
  "state_dict_tensor_total": 26768309,
  "train_args": {
   "batch": 384,
   "gate_bias": 0.0,
   "hold_frac": null,
   "lr": 0.0003,
   "model": "txe",
   "resume_from": null,
   "run": "TXE_ON_E3",
   "seed": 1,
   "shards_split": "e3_train",
   "state_tau": 16.0,
   "update_rule": "additive_clamp",
   "updates": 20000,
   "w_enum": 2.0,
   "w_other": 1.0
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  "train_corpus": "e3_train",
  "updates": 20000
 },
 "TXE_fin": {
  "admission_note": "TXE_v2c diverged and was killed before completion (amendment A5 auto-fail)",
  "admitted_checkpoint": "final.pt",
  "admitted_from_run": "TXE_v2",
  "batch": 384,
  "cfg": {
   "d": 384,
   "heads": 8,
   "layers": 10,
   "vocab": 8192,
   "window": 64
  },
  "group": "experiment1",
  "kind": "txe",
  "lr": 0.0003,
  "param_count_note": "params = distinct trainable parameters (the paper's matched-budget figure). The event encoder and record encoder share one tied 8192x384 token embedding, so state_dict lists it twice; state_dict_tensor_total is that raw sum and is ~3.15M larger for the 25M models.",
  "params": 23622581,
  "role": "memory-free control: current event only",
  "run": "TXE_fin",
  "seed": 1,
  "source_run_directory": "TXE_fin",
  "state_dict_tensor_total": 26768309,
  "train_args": {
   "batch": 384,
   "lr": 0.0003,
   "model": "txe",
   "run": "TXE_v2",
   "seed": 1,
   "updates": 20000
  },
  "train_corpus": "train",
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 }
}