intents_snips.json

{
  "dataset_reader": {
    "class_name": "snips_reader",
    "x": "text",
    "y": "intents",
    "data_path": "{DOWNLOADS_PATH}/snips"
  },
  "dataset_iterator": {
    "class_name": "snips_intents_iterator",
    "seed": 42
  },
  "chainer": {
    "in": [
      "x"
    ],
    "in_y": [
      "y"
    ],
    "pipe": [
      {
        "id": "classes_vocab",
        "class_name": "simple_vocab",
        "fit_on": [
          "y"
        ],
        "level": "token",
        "save_path": "{MODEL_PATH}/classes.dict",
        "load_path": "{MODEL_PATH}/classes.dict",
        "in": "y",
        "out": "y_ids"
      },
      {
        "in": "x",
        "out": "x_tok",
        "id": "my_tokenizer",
        "class_name": "nltk_tokenizer",
        "tokenizer": "wordpunct_tokenize"
      },
      {
        "in": "x_tok",
        "out": "x_emb",
        "id": "my_embedder",
        "class_name": "fasttext",
        "load_path": "{DOWNLOADS_PATH}/embeddings/dstc2_fastText_model.bin",
        "pad_zero": true
      },
      {
        "in": "y_ids",
        "out": "y_onehot",
        "class_name": "one_hotter",
        "depth": "#classes_vocab.len",
        "single_vector": true
      },
      {
        "in": [
          "x_emb"
        ],
        "in_y": [
          "y_onehot"
        ],
        "out": [
          "y_pred_probas"
        ],
        "main": true,
        "class_name": "keras_classification_model",
        "save_path": "{MODEL_PATH}/model",
        "load_path": "{MODEL_PATH}/model",
        "embedding_size": "#my_embedder.dim",
        "n_classes": "#classes_vocab.len",
        "kernel_sizes_cnn": [
          1,
          2,
          3
        ],
        "filters_cnn": 256,
        "optimizer": "Adam",
        "learning_rate": 0.01,
        "learning_rate_decay": 0.1,
        "loss": "binary_crossentropy",
        "coef_reg_cnn": 1e-4,
        "coef_reg_den": 1e-4,
        "dropout_rate": 0.5,
        "dense_size": 100,
        "model_name": "cnn_model"
      },
      {
        "in": "y_pred_probas",
        "out": "y_pred_ids",
        "class_name": "proba2labels",
        "max_proba": true
      },
      {
        "in": "y_pred_ids",
        "out": "y_pred_labels",
        "ref": "classes_vocab"
      }
    ],
    "out": [
      "y_pred_labels"
    ]
  },
  "train": {
    "epochs": 1000,
    "batch_size": 64,
    "metrics": [
      "accuracy",
      "f1_macro",
      {
        "name": "roc_auc",
        "inputs": ["y_onehot", "y_pred_probas"]
      }
    ],
    "validation_patience": 5,
    "val_every_n_epochs": 5,
    "log_every_n_epochs": 5,
    "show_examples": false,
    "evaluation_targets": [
      "train",
      "valid"
    ],
    "class_name": "nn_trainer"
  },
  "metadata": {
    "variables": {
      "ROOT_PATH": "~/.deeppavlov",
      "DOWNLOADS_PATH": "{ROOT_PATH}/downloads",
      "MODELS_PATH": "{ROOT_PATH}/models",
      "MODEL_PATH": "{MODELS_PATH}/classifiers/intents_snips_v9"
    },
    "download": [
{
        "url": "http://files.deeppavlov.ai/deeppavlov_data/embeddings/dstc2_fastText_model.bin",
        "subdir": "{DOWNLOADS_PATH}/embeddings"
      },
      {
        "url": "http://files.deeppavlov.ai/deeppavlov_data/classifiers/intents_snips_v9.tar.gz",
        "subdir": "{MODELS_PATH}/classifiers"
      }
    ]
  }
}