{
  "model_class": "physioex.models.chambon2018:Chambon2018Net",
  "model_kwargs": {
    "n_classes": 5,
    "in_channels": 1,
    "sf": 128,
    "n_times": 3840,
    "dropout": 0.25
  },
  "training": {
    "dataset": "mass",
    "dataset_kwargs": {
      "cohort": 3
    },
    "channels": [
      "EEG"
    ],
    "pipeline_preset": "raw",
    "pipeline_kwargs": {
      "target_fs": 128.0
    },
    "sequence_length": 3,
    "max_epochs": 100,
    "lr": 0.001,
    "weight_decay": 0,
    "batch_size": 128,
    "loss": "CrossEntropyLoss",
    "fold": 0,
    "early_stopping_patience": 5
  },
  "reference": "Chambon et al. 2018 - A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series (arXiv:1707.03321)"
}