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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": "innovation",
"bias_ratio": 0.1,
"predictor_rate": 0.1,
"neutral_cadence": 1,
"epochs": 1,
"train_limit": 2048,
"test_limit": 1024,
"batch_size": 128,
"training_iterations": 12,
"inference_iterations": 30,
"seed": 1988,
"device": "cuda",
"autodiff_used_for_learning": false
},
"metrics": [
{
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"train_cost": 36.51505360752344,
"test_accuracy": 0.0888671875,
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"corrector": {
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"neutral_observations": 16
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],
"final": {
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"neutral_observations": 16
},
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}
}
|
