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{
  "schema": "rain_ep_structured_bias_screen_v1",
  "author": {
    "repository": "https://github.com/rain-neuromorphics/energy-based-learning",
    "revision": "6b253fd8a5d267535f58ab79992256ef10031ceb"
  },
  "protocol": {
    "dataset": "FashionMNIST",
    "network": "author ConvHopfieldEnergy28 32-64-10",
    "algorithm": "positive equilibrium propagation",
    "mode": "constant",
    "bias_ratio": 0.1,
    "predictor_rate": 0.5,
    "neutral_cadence": 0,
    "calibration_batches": 1000,
    "calibration_observations": 1000,
    "calibration_seconds": 62.76313781738281,
    "epochs": 1,
    "train_limit": 10000,
    "test_limit": 2000,
    "batch_size": 128,
    "training_iterations": 12,
    "inference_iterations": 30,
    "seed": 1988,
    "device": "cuda",
    "determinism": "best_effort_warn_only",
    "autodiff_used_for_learning": false
  },
  "metrics": [
    {
      "epoch": 1,
      "train_accuracy": 0.2995,
      "train_cost": 0.4459439748764038,
      "test_accuracy": 0.3605,
      "test_cost": 0.4418565979003906,
      "finite": true,
      "corrector": {
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        "clean_rms": 0.012249627574435758,
        "bias_rms": 0.3237730231776297,
        "residual_bias_rms": 0.4122399944579638,
        "bias_to_clean_rms": 26.431254436936896,
        "residual_to_clean_rms": 33.65326757511257,
        "neutral_observations": 1000
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      "wall_seconds": 74.42809700965881
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  ],
  "epochs_completed": 1,
  "final": {
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    "train_cost": 0.4459439748764038,
    "test_accuracy": 0.3605,
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    "finite": true,
    "corrector": {
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      "clean_rms": 0.012249627574435758,
      "bias_rms": 0.3237730231776297,
      "residual_bias_rms": 0.4122399944579638,
      "bias_to_clean_rms": 26.431254436936896,
      "residual_to_clean_rms": 33.65326757511257,
      "neutral_observations": 1000
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    "wall_seconds": 74.42809700965881
  }
}