results: close Rain parameter-bias screen

1 files changed, 279 insertions, 0 deletions

diff --git a/results/ep_bias/s0_summary.json b/results/ep_bias/s0_summary.json
new file mode 100644
index 0000000..a7a61bf
--- /dev/null
+++ b/results/ep_bias/s0_summary.json
@@ -0,0 +1,279 @@
+{
+  "interpretation": "At bias ratio 0.1, fixed structured parameter-measurement bias makes the raw run nonfinite while same-RMS zero-mean noise remains trainable. The parameter-level affine predictor does not recover clean learning under online, 64-batch warm-up, or matched 1000-batch frozen calibration, so this adapter is closed rather than promoted.",
+  "observations": {
+    "clean_final_test_accuracy": 0.7905,
+    "constant_cal1000_frozen_first_epoch_test_accuracy": 0.3605,
+    "innovation_cal1000_frozen_first_epoch_test_accuracy": 0.3275,
+    "innovation_cal64_online_final_test_accuracy": 0.5595,
+    "innovation_online_final_test_accuracy": 0.6295,
+    "raw_structured_bias_nonfinite": true,
+    "same_rms_noise_final_test_accuracy": 0.685,
+    "same_rms_noise_remains_finite": true
+  },
+  "rows": {
+    "clean": {
+      "all_metrics_finite": true,
+      "best_test_accuracy": 0.802,
+      "epochs_completed": 10,
+      "final_corrector": {},
+      "final_test_accuracy": 0.7905,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "dataset": "FashionMNIST",
+        "device": "cuda",
+        "epochs": 10,
+        "inference_iterations": 30,
+        "mode": "clean",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 1,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    },
+    "constant_cal1000_frozen": {
+      "all_metrics_finite": true,
+      "best_test_accuracy": 0.3605,
+      "epochs_completed": 1,
+      "final_corrector": {
+        "bias_rms": 0.3237730231776297,
+        "bias_to_clean_rms": 26.431254436936896,
+        "clean_rms": 0.012249627574435758,
+        "neutral_observations": 1000,
+        "residual_bias_rms": 0.4122399944579638,
+        "residual_to_clean_rms": 33.65326757511257,
+        "step": 78
+      },
+      "final_test_accuracy": 0.3605,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "calibration_batches": 1000,
+        "calibration_observations": 1000,
+        "calibration_seconds": 62.76313781738281,
+        "dataset": "FashionMNIST",
+        "determinism": "best_effort_warn_only",
+        "device": "cuda",
+        "epochs": 1,
+        "inference_iterations": 30,
+        "mode": "constant",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 0,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    },
+    "innovation_cal1000_frozen": {
+      "all_metrics_finite": true,
+      "best_test_accuracy": 0.3275,
+      "epochs_completed": 1,
+      "final_corrector": {
+        "bias_rms": 0.3237200042135343,
+        "bias_to_clean_rms": 71.72440874952738,
+        "clean_rms": 0.004513386863097249,
+        "neutral_observations": 1000,
+        "residual_bias_rms": 0.2362901873060857,
+        "residual_to_clean_rms": 52.353187190325364,
+        "step": 78
+      },
+      "final_test_accuracy": 0.3275,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "calibration_batches": 1000,
+        "calibration_observations": 1000,
+        "calibration_seconds": 63.849170207977295,
+        "dataset": "FashionMNIST",
+        "determinism": "best_effort_warn_only",
+        "device": "cuda",
+        "epochs": 1,
+        "inference_iterations": 30,
+        "mode": "innovation",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 0,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    },
+    "innovation_cal64_online": {
+      "all_metrics_finite": true,
+      "best_test_accuracy": 0.6315,
+      "epochs_completed": 10,
+      "final_corrector": {
+        "bias_rms": 0.32612410406317766,
+        "neutral_observations": 854,
+        "residual_bias_rms": 0.0003998780642494185,
+        "step": 789
+      },
+      "final_test_accuracy": 0.5595,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "calibration_batches": 64,
+        "calibration_observations": 64,
+        "calibration_seconds": 4.21977424621582,
+        "dataset": "FashionMNIST",
+        "device": "cuda",
+        "epochs": 10,
+        "inference_iterations": 30,
+        "mode": "innovation",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 1,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    },
+    "innovation_online": {
+      "all_metrics_finite": true,
+      "best_test_accuracy": 0.6295,
+      "epochs_completed": 10,
+      "final_corrector": {
+        "bias_rms": 0.3385132732724078,
+        "neutral_observations": 790,
+        "residual_bias_rms": 0.00048530249773301345,
+        "step": 789
+      },
+      "final_test_accuracy": 0.6295,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "dataset": "FashionMNIST",
+        "device": "cuda",
+        "epochs": 10,
+        "inference_iterations": 30,
+        "mode": "innovation",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 1,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    },
+    "oracle": {
+      "all_metrics_finite": true,
+      "best_test_accuracy": 0.7995,
+      "epochs_completed": 10,
+      "final_corrector": {
+        "bias_rms": 0.15150278767133962,
+        "neutral_observations": 0,
+        "residual_bias_rms": 0.0,
+        "step": 789
+      },
+      "final_test_accuracy": 0.739,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "dataset": "FashionMNIST",
+        "device": "cuda",
+        "epochs": 10,
+        "inference_iterations": 30,
+        "mode": "oracle",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 1,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    },
+    "raw": {
+      "all_metrics_finite": false,
+      "best_test_accuracy": 0.1,
+      "epochs_completed": 10,
+      "final_corrector": {
+        "bias_rms": null,
+        "neutral_observations": 0,
+        "residual_bias_rms": null,
+        "step": 789
+      },
+      "final_test_accuracy": 0.1,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "calibration_batches": 0,
+        "calibration_observations": 0,
+        "calibration_seconds": 9.5367431640625e-07,
+        "dataset": "FashionMNIST",
+        "device": "cuda",
+        "epochs": 10,
+        "inference_iterations": 30,
+        "mode": "raw",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 1,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    },
+    "same_rms_noise": {
+      "all_metrics_finite": true,
+      "best_test_accuracy": 0.7035,
+      "epochs_completed": 10,
+      "final_corrector": {
+        "bias_rms": 0.29874716964496195,
+        "bias_to_clean_rms": 115.21319470829337,
+        "clean_rms": 0.002592994408334528,
+        "neutral_observations": 0,
+        "residual_bias_rms": 0.29872960535884535,
+        "residual_to_clean_rms": 115.20642096205614,
+        "step": 789
+      },
+      "final_test_accuracy": 0.685,
+      "protocol": {
+        "algorithm": "positive equilibrium propagation",
+        "autodiff_used_for_learning": false,
+        "batch_size": 128,
+        "bias_ratio": 0.1,
+        "calibration_batches": 0,
+        "calibration_observations": 0,
+        "calibration_seconds": 9.5367431640625e-07,
+        "dataset": "FashionMNIST",
+        "device": "cuda",
+        "epochs": 10,
+        "inference_iterations": 30,
+        "mode": "same_rms_noise",
+        "network": "author ConvHopfieldEnergy28 32-64-10",
+        "neutral_cadence": 1,
+        "predictor_rate": 0.5,
+        "seed": 1988,
+        "test_limit": 2000,
+        "train_limit": 10000,
+        "training_iterations": 12
+      }
+    }
+  },
+  "stage": "rain_ep_parameter_measurement_s0",
+  "status": "closed_negative_adapter_with_positive_bias_noise_control",
+  "test_policy": "development_test_subset_observed_each_epoch"
+}