{
  "schema_version": 1,
  "protocols": {
    "burstccn_cifar10_symplastic_paper_seed0": {
      "method": "BurstCCN",
      "dataset": "CIFAR-10",
      "seed": 0,
      "expected_epochs": 400,
      "repository_url": "https://github.com/neuralml/BurstCCN-journal",
      "source_revision": "9170e110b4d18729dc5bc5d517fc52eefcd04d69",
      "required_dataset_sha256": [
        "6d958be074577803d12ecdefd02955f39262c83c16fe9348329d7fe0b5c001ce"
      ],
      "expected_gpu": {
        "physical_index": "5",
        "name": "NVIDIA GeForce GTX 1080"
      },
      "paper_url": "https://www.biorxiv.org/content/10.64898/2026.06.16.732595v1",
      "published_accuracy_percent_mean": 82.97,
      "published_accuracy_percent_sd": 0.21,
      "selection_semantics": {
        "primary": "final epoch test accuracy",
        "validation_selected": "test accuracy at the epoch with minimum validation top-1 error",
        "test_selected": "maximum test accuracy over all epochs; reported separately"
      },
      "required_config": {
        "model.loss_type": "mse",
        "model.hidden_activation_function": "relu_rms",
        "model.output_activation_function": "softmax",
        "model.W.optimiser.lr": 0.002,
        "model.W.optimiser.momentum": 0.9,
        "model.W.optimiser.weight_decay": 0.0001,
        "model.Y.mode": "sym_W",
        "model.Y.grad_type": "kp",
        "model.Y.optimiser.lr": 0.001,
        "model.Q.mode": "sym_Y",
        "model.Q.grad_type": "kp",
        "model.Q.optimiser.lr": 0.001,
        "dataset.dataset_name": "cifar10",
        "dataset.use_validation": true,
        "training.seed": 0,
        "training.n_epochs": 400,
        "training.batch_size": 32,
        "training.label_smoothing": 0.05
      },
      "command": [
        "python",
        "train.py",
        "--config-name=cifar10_burstccn_kp",
        "dataset.root=/home/yurenh2/sdrn/data",
        "training.seed=0",
        "model.hidden_activation_function=relu_rms",
        "model.output_activation_function=softmax",
        "model.W.optimiser.lr=0.002",
        "model.Y.mode=sym_W",
        "model.Q.mode=sym_Y",
        "hydra.run.dir=/scratch/yurenh2/burstccn-native/cifar10_symplastic_paper_seed0"
      ]
    },
    "dualprop_cifar10_vgg16_a0_b0p1_seed1988": {
      "method": "Dual Propagation",
      "dataset": "CIFAR-10",
      "seed": 1988,
      "expected_epochs": 130,
      "repository_url": "https://github.com/Rasmuskh/dualprop_icml_2024",
      "source_revision": "7b2595b34421e1483a721dbfdeff8cdabda3a1ff",
      "required_dataset_sha256": [
        "6d958be074577803d12ecdefd02955f39262c83c16fe9348329d7fe0b5c001ce",
        "0b97b0a786c64f4cd0996cace20e81e189669aba9f4b4e517eb529f9c7105cec"
      ],
      "expected_gpu": {
        "physical_index": "7",
        "name": "NVIDIA GeForce GTX 1080"
      },
      "paper_url": "https://arxiv.org/abs/2402.08573",
      "published_accuracy_percent_mean": 92.41,
      "published_accuracy_percent_sd": 0.07,
      "selection_semantics": {
        "primary": "single test evaluation from the best-validation checkpoint",
        "validation_selected": "same as primary",
        "test_selected": "not available; test is evaluated only once"
      },
      "resolved_config": {
        "model": "VGG16",
        "alpha": 0.0,
        "beta": 0.1,
        "learning_algorithm": "dualprop-lagr-ff",
        "inference_sequence": "fwK",
        "inference_passes_nudged": 16,
        "batch_size": 100,
        "learning_rate": 0.025,
        "warmup_epochs": 10,
        "decay_epochs": 120,
        "momentum": 0.9,
        "weight_decay": 0.0005,
        "percent_train": 90,
        "percent_val": 10
      },
      "command": [
        "python",
        "train.py",
        "--model", "VGG16",
        "--dataset", "cifar10",
        "--num-epochs", "130",
        "--batch-size", "100",
        "--alpha", "0.0",
        "--beta", "0.1",
        "--loss", "sce",
        "--inference-sequence", "fwK",
        "--inference-passes-nudged", "16",
        "--learning-rate", "0.025",
        "--learning-rate-final", "0.000002",
        "--warmup-learning-rate", "0.001",
        "--learning-algorithm", "dualprop-lagr-ff",
        "--activation", "relu",
        "--decay-epochs", "120",
        "--warmup-epochs", "10",
        "--momentum", "0.9",
        "--weight-decay", "5e-4",
        "--dtype", "float32",
        "--param-dtype", "float32",
        "--percent-train", "90",
        "--percent-val", "10",
        "--seeds", "1988",
        "--experiment-name", "sdil-dp-full-a0-b0p1-seed1988-v1"
      ]
    }
  }
}