{
  "bundle": {
    "bundle_subdir": "bundle"
  },
  "hub": {
    "repo_id": null,
    "revision": null
  },
  "io": {
    "input_domain": null,
    "inputs": {
      "channel_meanings_tree": {
        "parameters": [
          "effective temperature",
          "surface gravity",
          "metallicity [Fe/H]",
          "microturbulence velocity",
          "cosine of viewing angle"
        ],
        "wavelengths": null
      },
      "channel_names_tree": {
        "parameters": [
          "teff",
          "logg",
          "[Fe/H]",
          "vmicro",
          "mu"
        ],
        "wavelengths": null
      },
      "channel_units_tree": {
        "parameters": [
          "dimensionless",
          "dimensionless",
          "dimensionless",
          "dimensionless",
          "dimensionless"
        ],
        "wavelengths": null
      },
      "leaf_meanings_tree": {
        "parameters": "min-max scaled model input parameters; see reference_scaling_inputs for raw parameter bounds and bundle_extras.fixed_parameter_values for any source-grid parameters held fixed outside the model input",
        "wavelengths": "min-max scaled log10 wavelength; the user applies log10 before reference_scaling_inputs"
      },
      "leaf_units_tree": {
        "parameters": null,
        "wavelengths": "dimensionless"
      },
      "structure_tree": {
        "parameters": null,
        "wavelengths": null
      }
    },
    "outputs": {
      "channel_meanings_tree": {
        "flux": [
          "min-max scaled log10 line intensity from source array flux",
          "min-max scaled log10 continuum intensity from source array continuum"
        ]
      },
      "channel_names_tree": {
        "flux": [
          "log_flux_lines",
          "log_flux_continuum"
        ]
      },
      "channel_units_tree": {
        "flux": [
          "dimensionless",
          "dimensionless"
        ]
      },
      "leaf_meanings_tree": {
        "flux": "two min-max scaled log10 intensity channels from the Maja archive arrays flux and continuum"
      },
      "leaf_units_tree": {
        "flux": "dimensionless"
      },
      "structure_tree": {
        "flux": null
      }
    },
    "reference_scaling_inputs": null,
    "reference_scaling_outputs": null
  },
  "model": {
    "init_hints": {
      "parameter_dim": 5
    },
    "name": "transformer_payne",
    "params": {
      "channels": 2,
      "dim": 48,
      "dim_ff_multiplier": 2,
      "dim_head": 16,
      "dtype": "float32",
      "max_period": 1.0,
      "min_period": 0.0001,
      "no_layers": 3,
      "no_tokens": 8
    }
  },
  "optim": {
    "b1": 0.9,
    "b2": 0.999,
    "decay_steps": 0,
    "eps": 1e-08,
    "grad_clip": 0.0,
    "lr": 0.001,
    "lr_scaling": null,
    "name": "soap",
    "precondition_1d": false,
    "precondition_frequency": 10,
    "scale_embedding_lr": 1.0,
    "schedule": "cosine",
    "warmup_steps": 50000,
    "weight_decay": 0.0001
  },
  "schema_version": 1,
  "seed": 0,
  "solver": {
    "name": "auto",
    "params": {}
  },
  "task": {
    "name": "regression",
    "params": {
      "loss": "mse",
      "metric_axes": {
        "channel": [
          0
        ],
        "global": "all"
      },
      "metrics": [
        "mse",
        "mae"
      ]
    }
  },
  "training": {
    "batch_size": 128,
    "checkpoint_interval_steps": 20000,
    "checkpoint_steps": null,
    "evaluation_interval_steps": 10000,
    "evaluation_steps": null,
    "logging_interval_steps": 2000,
    "logging_steps": null,
    "max_saved_checkpoints": 5,
    "num_steps": 500000,
    "shuffle": true,
    "shuffle_seed": 0,
    "steps_per_epoch": null,
    "val_fraction": 0.0,
    "workdir": "./runs/from_bundle"
  }
}