TALENT Model Hyperparameter Viewer

📂 LinearRegression
Default Configuration
No default parameters available.
Search Space
No search space defined.
📂 LogReg
Default Configuration
Model Parameters
{
  "penalty": "l2",
  "max_iter": 5000
}
Search Space
Model Search Space
{
  "C": [
    "loguniform",
    1e-05,
    5
  ],
  "penalty": [
    "categorical",
    [
      "l2",
      null
    ]
  ],
  "max_iter": [
    "int",
    50,
    500
  ]
}
📂 NCM
Default Configuration
No default parameters available.
Search Space
No search space defined.
📂 NaiveBayes
Default Configuration
No default parameters available.
Search Space
No search space defined.
📂 PFN-v2
Default Configuration
General Parameters
{
  "sample_size": 10000
}
Search Space
General Search Space
{
  "sample_size": 10000
}
📂 RandomForest
Default Configuration
Model Parameters
{
  "max_depth": 12,
  "n_estimators": 2000
}
Search Space
Model Search Space
{
  "min_samples_split": [
    "int",
    2,
    10
  ],
  "min_samples_leaf": [
    "int",
    1,
    10
  ]
}
📂 amformer
Default Configuration
Model Parameters
{
  "dim": 192,
  "depth": 3,
  "heads": 8,
  "attn_dropout": 0.2,
  "ff_dropout": 0.1,
  "groups": [
    54,
    54,
    54
  ],
  "sum_num_per_group": [
    32,
    16,
    8
  ],
  "prod_num_per_group": [
    6,
    6,
    6
  ],
  "cluster": true,
  "target_mode": "mix",
  "token_descent": false,
  "num_special_tokens": 2
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "depth": [
    "int",
    1,
    4
  ],
  "dim": [
    "categorical",
    [
      8,
      16,
      32,
      64,
      128
    ]
  ],
  "attn_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "ff_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "num_special_tokens": [
    "int",
    1,
    4
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 autoint
Default Configuration
Model Parameters
{
  "n_layers": 3,
  "d_token": 64,
  "n_heads": 8,
  "attention_dropout": 0.2,
  "residual_dropout": 0.0,
  "activation": "relu",
  "prenormalization": false,
  "initialization": "kaiming",
  "kv_compression": null,
  "kv_compression_sharing": null
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "n_layers": [
    "int",
    1,
    6
  ],
  "d_token": [
    "categorical",
    [
      8,
      16,
      32,
      64,
      128
    ]
  ],
  "residual_dropout": [
    "?uniform",
    0.0,
    0.0,
    0.2
  ],
  "attention_dropout": [
    "uniform",
    0.0,
    0.5
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 bishop
Default Configuration
Model Parameters
{
  "emb_dim": 32,
  "out_dim": 24,
  "patch_dim": 8,
  "factor": 10,
  "n_agg": 4,
  "d_model": 512,
  "d_ff": 256,
  "n_heads": 4,
  "e_layer": 2,
  "d_layer": 2,
  "emb_dropout": 0.1,
  "dropout": 0.2,
  "share_div": 8,
  "mlp_dropout": 0.2,
  "hopfield": true
}
Training Parameters
{
  "lr": 5e-05,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "emb_dim": [
    "categorical",
    [
      16,
      24,
      32,
      48,
      64,
      128,
      256,
      320
    ]
  ],
  "out_dim": [
    "categorical",
    [
      2,
      4,
      8,
      16,
      32,
      64,
      128
    ]
  ],
  "patch_dim": [
    "categorical",
    [
      1,
      2,
      4,
      6,
      8,
      12,
      16,
      24
    ]
  ],
  "n_agg": [
    "categorical",
    [
      2,
      3,
      4,
      5,
      6,
      7,
      8
    ]
  ],
  "factor": [
    "categorical",
    [
      5,
      10,
      15
    ]
  ],
  "d_model": [
    "categorical",
    [
      64,
      128,
      256,
      512,
      1024
    ]
  ],
  "d_ff": [
    "categorical",
    [
      128,
      256,
      512,
      1024
    ]
  ],
  "n_heads": [
    "categorical",
    [
      2,
      4,
      6,
      8,
      10,
      12
    ]
  ],
  "e_layer": [
    "categorical",
    [
      2,
      3,
      4,
      5
    ]
  ],
  "d_layer": [
    "categorical",
    [
      0,
      1
    ]
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-06,
    0.0001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 catboost
Default Configuration
Fit Parameters
{
  "logging_level": "Silent"
}
Model Parameters
{
  "early_stopping_rounds": 50,
  "n_estimators": 2000,
  "od_pval": 0.001
}
Search Space
Model Search Space
{
  "bagging_temperature": [
    "uniform",
    0.0,
    1.0
  ],
  "depth": [
    "int",
    3,
    10
  ],
  "l2_leaf_reg": [
    "loguniform",
    1.0,
    10.0
  ],
  "leaf_estimation_iterations": [
    "int",
    1,
    10
  ],
  "learning_rate": [
    "loguniform",
    1e-05,
    1
  ]
}
📂 danets
Default Configuration
Model Parameters
{
  "base_outdim": 64,
  "n_layers": 20,
  "dropout": 0.1
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0.0002
}
General Parameters
{
  "k": 5,
  "virtual_batch_size": 256
}
Search Space
Model Search Space
{
  "n_layers": [
    "int",
    6,
    32
  ],
  "dropout": [
    "?uniform",
    0.0,
    0.0,
    0.5
  ],
  "base_outdim": [
    "int",
    64,
    128
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 dcn2
Default Configuration
Model Parameters
{
  "d": 512,
  "n_hidden_layers": 2,
  "n_cross_layers": 3,
  "hidden_dropout": 0.1,
  "cross_dropout": 0.1,
  "stacked": false,
  "d_embedding": 64
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0.0002
}
Search Space
Model Search Space
{
  "d": [
    "int",
    64,
    512
  ],
  "d_embedding": [
    "int",
    64,
    512
  ],
  "hidden_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "cross_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "n_cross_layers": [
    "int",
    1,
    8
  ],
  "n_hidden_layers": [
    "int",
    1,
    8
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 dnnr
Default Configuration
Model Parameters
{
  "n_neighbors": 3,
  "n_derivative_neighbors": 128,
  "order": "1",
  "solver": "linear_regression",
  "index": "annoy"
}
Search Space
Model Search Space
{
  "n_neighbors": [
    "int",
    3,
    3
  ],
  "n_derivative_neighbors": [
    "int",
    32,
    1024
  ],
  "order": [
    "categorical",
    [
      "1",
      "2diag"
    ]
  ],
  "solver": [
    "categorical",
    [
      "linear_regression",
      "scipy_lsqr",
      "numpy",
      "ridge",
      "lasso"
    ]
  ],
  "index": [
    "categorical",
    [
      "annoy"
    ]
  ]
}
📂 dummy
Default Configuration
No default parameters available.
Search Space
No search space defined.
📂 excelformer
Default Configuration
Model Parameters
{
  "prenormalization": true,
  "kv_compression": null,
  "kv_compression_sharing": null,
  "token_bias": true,
  "ffn_dropout": 0,
  "attention_dropout": 0.3,
  "residual_dropout": 0.0,
  "n_layers": 3,
  "n_heads": 32,
  "d_token": 256,
  "init_scale": 0.01
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0,
  "mix_type": "none"
}
Search Space
Model Search Space
{
  "n_layers": [
    "int",
    2,
    5
  ],
  "d_token": [
    "categorical",
    [
      8,
      16,
      32,
      64,
      128
    ]
  ],
  "residual_dropout": [
    "?uniform",
    0.0,
    0.0,
    0.5
  ],
  "attention_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "ffn_dropout": [
    "uniform",
    0.0,
    0.5
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ],
  "mix_type": [
    "categorical",
    [
      "none",
      "feat_mix",
      "hidden_mix"
    ]
  ]
}
📂 ftt
Default Configuration
Model Parameters
{
  "token_bias": true,
  "n_layers": 3,
  "d_token": 192,
  "n_heads": 8,
  "d_ffn_factor": 1.3333333333333333,
  "attention_dropout": 0.2,
  "ffn_dropout": 0.1,
  "residual_dropout": 0.0,
  "activation": "reglu",
  "prenormalization": false,
  "initialization": "kaiming",
  "kv_compression": null,
  "kv_compression_sharing": null
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "n_layers": [
    "int",
    1,
    4
  ],
  "d_token": [
    "categorical",
    [
      8,
      16,
      32,
      64,
      128
    ]
  ],
  "residual_dropout": [
    "?uniform",
    0.0,
    0.0,
    0.2
  ],
  "attention_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "ffn_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "d_ffn_factor": [
    "uniform",
    0.6666666666666667,
    2.6666666666666665
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 grande
Default Configuration
Model Parameters
{
  "depth": 5,
  "n_estimators": 2048,
  "from_logits": true,
  "use_class_weights": true,
  "selected_variables": 0.8,
  "data_subset_fraction": 1.0,
  "dropout": 0.0,
  "bootstrap": false
}
Training Parameters
{
  "lr": 0.001,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "depth": [
    "int",
    3,
    7
  ],
  "n_estimators": [
    "int",
    512,
    2048
  ],
  "selected_variables": [
    "categorical",
    [
      1,
      0.75,
      0.5
    ]
  ],
  "data_subset_fraction": [
    "categorical",
    [
      0.8,
      1.0
    ]
  ],
  "dropout": [
    "categorical",
    [
      0.0,
      0.25
    ]
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    0.0001,
    0.25
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 grownet
Default Configuration
Ensemble_model Parameters
{
  "lr": 1.0,
  "d_embedding": 128
}
Model Parameters
{
  "hidden_d": 128,
  "sparse": false
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0.0002,
  "epochs_per_stage": 1,
  "lr_scaler": 3,
  "correct_epoch": 1
}
Search Space
Ensemble_model Search Space
{
  "d_embedding": [
    "int",
    32,
    512
  ]
}
Model Search Space
{
  "hidden_d": [
    "int",
    32,
    512
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ],
  "epochs_per_stage": [
    "int",
    1,
    2
  ],
  "correct_epoch": [
    "int",
    1,
    2
  ]
}
📂 hyperfast
Default Configuration
No default parameters available.
Search Space
No search space defined.
📂 knn
Default Configuration
Model Parameters
{
  "weights": "distance",
  "algorithm": "auto",
  "p": 2,
  "metric": "minkowski"
}
Search Space
Model Search Space
{
  "n_neighbors": [
    "int",
    1,
    128
  ],
  "weights": [
    "categorical",
    [
      "uniform",
      "distance"
    ]
  ],
  "p": [
    "categorical",
    [
      1,
      1.5,
      2,
      2.5,
      3
    ]
  ]
}
📂 lightgbm
Default Configuration
Model Parameters
{
  "n_estimators": 2000
}
Search Space
Model Search Space
{
  "num_leaves": [
    "int",
    10,
    100
  ],
  "max_depth": [
    "int",
    3,
    10
  ],
  "learning_rate": [
    "loguniform",
    0.001,
    1.0
  ],
  "min_child_weight": [
    "loguniform",
    1e-05,
    0.1
  ],
  "min_child_samples": [
    "int",
    2,
    100
  ],
  "subsample": [
    "uniform",
    0.5,
    1.0
  ],
  "colsample_bytree": [
    "uniform",
    0.5,
    1.0
  ],
  "reg_lambda": [
    "?loguniform",
    0.0,
    1e-05,
    1.0
  ]
}
📂 linear
Default Configuration
Training Parameters
{
  "lr": 0.001,
  "weight_decay": 0.0002
}
Search Space
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.01
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 mlp
Default Configuration
Model Parameters
{
  "d_layers": [
    384,
    384
  ],
  "dropout": 0.1
}
Training Parameters
{
  "lr": 0.0003,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "d_layers": [
    "$mlp_d_layers",
    1,
    8,
    64,
    512
  ],
  "dropout": [
    "?uniform",
    0.0,
    0.0,
    0.5
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.01
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 mlp_plr
Default Configuration
Model Parameters
{
  "d_layers": [
    510,
    263,
    363
  ],
  "dropout": 0.2,
  "num_embeddings": {
    "type": "PLREmbeddings",
    "n_frequencies": 77,
    "frequency_scale": 0.04431360576139521,
    "d_embedding": 34,
    "lite": true
  }
}
Training Parameters
{
  "lr": 0.001,
  "weight_decay": 0.0002
}
Search Space
Model Search Space
{
  "d_layers": [
    "$mlp_d_layers",
    1,
    8,
    64,
    1024
  ],
  "dropout": [
    "?uniform",
    0.0,
    0.0,
    0.5
  ],
  "num_embeddings": {
    "n_frequencies": [
      "int",
      16,
      96
    ],
    "frequency_scale": [
      "loguniform",
      0.01,
      100.0
    ],
    "d_embedding": [
      "int",
      16,
      64
    ]
  }
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.01
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 modernNCA
Default Configuration
Model Parameters
{
  "dim": 128,
  "dropout": 0.1,
  "d_block": 512,
  "n_blocks": 0,
  "temperature": 1,
  "num_embeddings": {
    "type": "PLREmbeddings",
    "n_frequencies": 77,
    "frequency_scale": 0.04431360576139521,
    "d_embedding": 34,
    "lite": true
  },
  "sample_rate": 0.5
}
Training Parameters
{
  "lr": 0.01,
  "weight_decay": 0.0002
}
Search Space
Model Search Space
{
  "dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "d_block": [
    "int",
    64,
    1024
  ],
  "n_blocks": [
    "?int",
    0,
    0,
    2
  ],
  "dim": [
    "int",
    64,
    1024
  ],
  "num_embeddings": {
    "n_frequencies": [
      "int",
      16,
      96
    ],
    "frequency_scale": [
      "loguniform",
      0.005,
      10.0
    ],
    "d_embedding": [
      "int",
      16,
      64
    ]
  },
  "sample_rate": [
    "uniform",
    0.05,
    0.6
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 node
Default Configuration
Model Parameters
{
  "num_layers": 1,
  "depth": 6,
  "layer_dim": 1024,
  "tree_dim": 2,
  "choice_function": "sparsemax",
  "bin_function": "sparsemoid"
}
Training Parameters
{
  "lr": 0.001,
  "weight_decay": 0.0
}
Search Space
Model Search Space
{
  "num_layers": [
    "int",
    1,
    4
  ],
  "depth": [
    "int",
    4,
    6
  ],
  "tree_dim": [
    "int",
    2,
    3
  ],
  "layer_dim": [
    "categorical",
    [
      512,
      1024
    ]
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 protogate
Default Configuration
Model Parameters
{
  "a": 1,
  "sigma": 0.5,
  "hidden_layer_list": [
    200
  ]
}
Training Parameters
{
  "lr": 0.1,
  "weight_decay": 1e-05,
  "pred_k": 3,
  "lam": 0.001,
  "l1_coef": 0.0002,
  "pred_coef": 1,
  "sorting_tau": 16,
  "feature_selection": true
}
Search Space
Model Search Space
{
  "hidden_layer_list": [
    "$mlp_d_layers",
    1,
    4,
    64,
    512
  ]
}
Training Search Space
{
  "lr": [
    "categorical",
    [
      0.05,
      0.075,
      0.1
    ]
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ],
  "l1_coef": [
    "categorical",
    [
      0.0001,
      0.0002,
      0.0003,
      0.0004,
      0.0006
    ]
  ],
  "pred_k": [
    "categorical",
    [
      1,
      2,
      3,
      4,
      5
    ]
  ]
}
📂 ptarl
Default Configuration
Model Parameters
{
  "n_clusters": 20,
  "d_embedding": 64,
  "d_layers": [
    256,
    256
  ],
  "dropout": 0.2,
  "regularize": true
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0.0002
}
General Parameters
{
  "ot_weight": 0.25,
  "diversity_weight": 0.25,
  "r_weight": 0.25,
  "diversity": true
}
Search Space
Model Search Space
{
  "d_layers": [
    "$mlp_d_layers",
    1,
    3,
    64,
    512
  ],
  "dropout": [
    "?uniform",
    0.0,
    0.0,
    0.5
  ],
  "d_embedding": [
    "int",
    64,
    128
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 realmlp
Default Configuration
Model Parameters
{
  "num_emb_type": "pbld",
  "add_front_scale": true,
  "lr": 0.04,
  "p_drop": 0.15,
  "act": "selu",
  "hidden_sizes": [
    256,
    256,
    256
  ],
  "wd": 0.02,
  "plr_sigma": 0.1,
  "ls_eps": 0.1
}
Search Space
Model Search Space
{
  "num_emb_type": [
    "categorical",
    [
      "none",
      "pbld",
      "pl",
      "plr"
    ]
  ],
  "add_front_scale": [
    "categorical",
    [
      true,
      false
    ]
  ],
  "lr": [
    "loguniform",
    0.02,
    0.3
  ],
  "p_drop": [
    "categorical",
    [
      0.0,
      0.15,
      0.3
    ]
  ],
  "act": [
    "categorical",
    [
      "selu",
      "relu",
      "mish"
    ]
  ],
  "hidden_sizes": [
    "categorical",
    [
      [
        256,
        256,
        256
      ],
      [
        64,
        64,
        64,
        64,
        64
      ],
      [
        512
      ]
    ]
  ],
  "wd": [
    "categorical",
    [
      0.0,
      0.02
    ]
  ],
  "plr_sigma": [
    "loguniform",
    0.05,
    0.5
  ],
  "ls_eps": [
    "categorical",
    [
      0.0,
      0.1
    ]
  ]
}
📂 resnet
Default Configuration
Model Parameters
{
  "d": 192,
  "d_hidden_factor": 2.0,
  "hidden_dropout": 0.3,
  "n_layers": 2,
  "residual_dropout": 0.0,
  "activation": "relu",
  "normalization": "batchnorm"
}
Training Parameters
{
  "lr": 0.0003,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "n_layers": [
    "int",
    1,
    8
  ],
  "d": [
    "int",
    64,
    512
  ],
  "d_hidden_factor": [
    "uniform",
    1.0,
    4.0
  ],
  "hidden_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "residual_dropout": [
    "?uniform",
    0.0,
    0.0,
    0.5
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.01
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 saint
Default Configuration
Model Parameters
{
  "depth": 6,
  "heads": 8,
  "dim": 32,
  "attn_dropout": 0.0,
  "ff_dropout": 0.0,
  "attentiontype": "colrow",
  "cont_embeddings": "MLP"
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0.01
}
Search Space
Model Search Space
{
  "depth": [
    "categorical",
    [
      4,
      6
    ]
  ],
  "heads": [
    "categorical",
    [
      4,
      8
    ]
  ],
  "dim": [
    "categorical",
    [
      16,
      32,
      64
    ]
  ],
  "attn_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "ff_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "attentiontype": [
    "?categorical",
    "colrow",
    [
      "colrow",
      "row",
      "col"
    ]
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    3e-05,
    0.001
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.0001
  ]
}
📂 snn
Default Configuration
Model Parameters
{
  "d_layers": [
    384,
    384
  ],
  "dropout": 0.2,
  "d_embedding": 64
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0.0002
}
Search Space
Model Search Space
{
  "d_layers": [
    "$mlp_d_layers",
    2,
    16,
    1,
    512
  ],
  "dropout": [
    "?uniform",
    0.0,
    0.0,
    0.1
  ],
  "d_embedding": [
    "int",
    64,
    512
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.01
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 svm
Default Configuration
No default parameters available.
Search Space
Model Search Space
{
  "C": [
    "loguniform",
    1e-05,
    100000.0
  ]
}
📂 switchtab
Default Configuration
Model Parameters
{
  "num_heads": 2,
  "alpha": 1.0
}
Training Parameters
{
  "lr": 0.0003,
  "weight_decay": 0.0002
}
Search Space
Model Search Space
{
  "alpha": [
    "loguniform",
    0.01,
    100
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-06,
    0.001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 t2gformer
Default Configuration
Model Parameters
{
  "token_bias": true,
  "n_layers": 3,
  "d_token": 192,
  "n_heads": 8,
  "d_ffn_factor": 1.3333333333333333,
  "attention_dropout": 0.2,
  "ffn_dropout": 0.1,
  "residual_dropout": 0.0,
  "activation": "reglu",
  "prenormalization": false,
  "initialization": "kaiming",
  "kv_compression": null,
  "kv_compression_sharing": null,
  "sym_weight": true,
  "sym_topology": false,
  "nsi": true
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 1e-05,
  "frozen_switch": true
}
Search Space
Model Search Space
{
  "n_layers": [
    "int",
    1,
    4
  ],
  "d_token": [
    "categorical",
    [
      8,
      16,
      32,
      64,
      128
    ]
  ],
  "residual_dropout": [
    "?uniform",
    0.0,
    0.0,
    0.2
  ],
  "attention_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "ffn_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "d_ffn_factor": [
    "uniform",
    0.6666666666666667,
    2.6666666666666665
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ],
  "frozen_switch": [
    "categorical",
    [
      true,
      false
    ]
  ]
}
📂 tabautopnpnet
Default Configuration
Model Parameters
{
  "num_fourier_features": 100,
  "max_poly_terms": 5,
  "poly_type": "chebyshev",
  "hidden_size": 256,
  "use_residual": true
}
Training Parameters
{
  "lr": 0.05,
  "weight_decay": 0.001
}
Search Space
Model Search Space
{
  "num_fourier_features": [
    10,
    25,
    50,
    75,
    100
  ],
  "max_poly_terms": [
    2,
    3,
    5,
    7,
    10
  ],
  "poly_type": [
    "chebyshev",
    "legendre",
    "hermite",
    "laguerre"
  ],
  "hidden_size": [
    64,
    128,
    256,
    512
  ],
  "use_residual": [
    false,
    true
  ]
}
Training Search Space
{
  "lr": [
    0.0005,
    0.005,
    0.05
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 tabcaps
Default Configuration
Model Parameters
{
  "lr": 0.001,
  "weight_decay": 0.0002,
  "sub_class": 3,
  "init_dim": 16,
  "primary_capsule_size": 16,
  "digit_capsule_size": 16,
  "leaves": 16
}
Search Space
Model Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ],
  "sub_class": [
    "int",
    1,
    5
  ],
  "init_dim": [
    "int",
    32,
    128
  ],
  "primary_capsule_size": [
    "int",
    4,
    32
  ],
  "digit_capsule_size": [
    "int",
    4,
    32
  ],
  "leaves": [
    "int",
    16,
    64
  ]
}
📂 tabicl
Default Configuration
No default parameters available.
Search Space
No search space defined.
📂 tabm
Default Configuration
Model Parameters
{
  "arch_type": "tabm",
  "k": 32,
  "num_embeddings": {
    "type": "PLREmbeddings",
    "n_frequencies": 77,
    "frequency_scale": 0.04431360576139521,
    "d_embedding": 34,
    "lite": true
  },
  "backbone": {
    "type": "MLP",
    "n_blocks": 2,
    "d_block": 384,
    "dropout": 0.1
  }
}
Training Parameters
{
  "lr": 0.0003,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "num_embeddings": {
    "n_frequencies": [
      "int",
      16,
      96
    ],
    "frequency_scale": [
      "loguniform",
      0.005,
      10.0
    ],
    "d_embedding": [
      "int",
      16,
      64
    ]
  },
  "backbone": {
    "n_blocks": [
      "int",
      1,
      5
    ],
    "d_block": [
      "int",
      64,
      1024
    ],
    "dropout": [
      "uniform",
      0.0,
      0.5
    ]
  }
}
Training Search Space
{
  "lr": [
    "loguniform",
    0.0001,
    0.005
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    0.0001,
    0.1
  ]
}
📂 tabnet
Default Configuration
Model Parameters
{
  "lr": 0.01,
  "gamma": 1.3,
  "n_steps": 3,
  "n_independent": 2,
  "n_shared": 2,
  "momentum": 0.02
}
Search Space
Model Search Space
{
  "lr": [
    "uniform",
    0.001,
    0.01
  ],
  "gamma": [
    "uniform",
    1,
    2
  ],
  "n_steps": [
    "int",
    3,
    10
  ],
  "n_independent": [
    "int",
    1,
    5
  ],
  "n_shared": [
    "int",
    1,
    5
  ],
  "momentum": [
    "uniform",
    0.01,
    0.4
  ]
}
📂 tabpfn
Default Configuration
General Parameters
{
  "sample_size": 3000
}
Search Space
No search space defined.
📂 tabptm
Default Configuration
Model Parameters
{
  "d_layers": [
    510,
    263,
    363
  ],
  "dropout": 0.2
}
Training Parameters
{
  "lr": 0.001,
  "weight_decay": 0.0002
}
Search Space
No search space defined.
📂 tabr
Default Configuration
Model Parameters
{
  "num_embeddings": {
    "type": "PLREmbeddings",
    "n_frequencies": 77,
    "frequency_scale": 0.04431360576139521,
    "d_embedding": 34,
    "lite": true
  },
  "d_main": 265,
  "context_dropout": 0.38920071545944357,
  "d_multiplier": 2.0,
  "encoder_n_blocks": 0,
  "predictor_n_blocks": 1,
  "mixer_normalization": "auto",
  "dropout0": 0.38852797479169876,
  "dropout1": 0.0,
  "normalization": "LayerNorm",
  "activation": "ReLU"
}
Training Parameters
{
  "lr": 0.0003121273641315169,
  "weight_decay": 1.2260352006404615e-06
}
Search Space
Model Search Space
{
  "d_main": [
    "int",
    96,
    384
  ],
  "context_dropout": [
    "uniform",
    0.0,
    0.6
  ],
  "encoder_n_blocks": [
    "int",
    0,
    1
  ],
  "predictor_n_blocks": [
    "int",
    1,
    2
  ],
  "dropout0": [
    "uniform",
    0.0,
    0.6
  ],
  "num_embeddings": {
    "n_frequencies": [
      "int",
      16,
      96
    ],
    "frequency_scale": [
      "loguniform",
      0.01,
      100.0
    ],
    "d_embedding": [
      "int",
      16,
      64
    ]
  }
}
Training Search Space
{
  "lr": [
    "loguniform",
    3e-05,
    0.001
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 tabtransformer
Default Configuration
Model Parameters
{
  "dim": 32,
  "depth": 6,
  "heads": 8,
  "attn_dropout": 0.08,
  "ff_dropout": 0.3
}
Training Parameters
{
  "lr": 0.0001,
  "weight_decay": 0.0002
}
Search Space
Model Search Space
{
  "dim": [
    "categorical",
    [
      32,
      64,
      128,
      256
    ]
  ],
  "depth": [
    "categorical",
    [
      1,
      2,
      3,
      6,
      12
    ]
  ],
  "heads": [
    "categorical",
    [
      2,
      4,
      8
    ]
  ],
  "attn_dropout": [
    "uniform",
    0.0,
    0.5
  ],
  "ff_dropout": [
    "uniform",
    0.0,
    0.5
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.1
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 tangos
Default Configuration
Model Parameters
{
  "d_layers": [
    256,
    256,
    256
  ],
  "dropout": 0.1,
  "lambda1": 1,
  "lambda2": 0.01,
  "subsample": 50
}
Training Parameters
{
  "lr": 0.001,
  "weight_decay": 0.0002
}
Search Space
Model Search Space
{
  "d_layers": [
    "$mlp_d_layers",
    1,
    8,
    64,
    512
  ],
  "dropout": [
    "?uniform",
    0.0,
    0.0,
    0.5
  ],
  "lambda1": [
    "loguniform",
    0.001,
    10
  ],
  "lambda2": [
    "loguniform",
    0.0001,
    1
  ],
  "subsample": [
    "int",
    30,
    100
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    0.0001,
    0.001
  ],
  "weight_decay": [
    "?loguniform",
    0.0,
    1e-06,
    0.001
  ]
}
📂 trompt
Default Configuration
Model Parameters
{
  "P": 128,
  "d": 128,
  "n_cycles": 6
}
Training Parameters
{
  "lr": 0.0003,
  "weight_decay": 1e-05
}
Search Space
Model Search Space
{
  "n_cycles": [
    "int",
    3,
    8
  ],
  "d": [
    "categorical",
    [
      32,
      64,
      128,
      256
    ]
  ],
  "P": [
    "categorical",
    [
      32,
      64,
      128,
      256
    ]
  ]
}
Training Search Space
{
  "lr": [
    "loguniform",
    1e-05,
    0.001
  ],
  "weight_decay": [
    "loguniform",
    1e-06,
    0.001
  ]
}
📂 xgboost
Default Configuration
Fit Parameters
{
  "verbose": false
}
Model Parameters
{
  "subsample": 0.8,
  "colsample_bytree": 0.8,
  "early_stopping_rounds": 50,
  "booster": "gbtree",
  "n_estimators": 2000,
  "n_jobs": -1,
  "tree_method": "hist"
}
Search Space
Model Search Space
{
  "alpha": [
    "?loguniform",
    0,
    1e-08,
    100.0
  ],
  "colsample_bylevel": [
    "uniform",
    0.5,
    1.0
  ],
  "colsample_bytree": [
    "uniform",
    0.5,
    1.0
  ],
  "gamma": [
    "?loguniform",
    0,
    1e-08,
    100.0
  ],
  "lambda": [
    "?loguniform",
    0,
    1e-08,
    100.0
  ],
  "learning_rate": [
    "loguniform",
    1e-05,
    1
  ],
  "max_depth": [
    "int",
    3,
    10
  ],
  "min_child_weight": [
    "loguniform",
    1e-08,
    100000.0
  ],
  "subsample": [
    "uniform",
    0.5,
    1.0
  ]
}