rubert_sentiment.json

{
  "dataset_reader": {
    "class_name": "basic_classification_reader",
    "x": "text",
    "y": "sentiment",
    "data_path": "/content/drive/MyDrive/BERT/train/",
    "train": "train.csv",
    "valid": "valid.csv"
  },
  "dataset_iterator": {
    "class_name": "basic_classification_iterator",
    "seed": 42
  },
  "chainer": {
    "in": [
      "x"
    ],
    "in_y": [
      "y"
    ],
    "pipe": [
      {
        "id": "classes_vocab",
        "class_name": "simple_vocab",
        "fit_on": [
          "y"
        ],
        "save_path": "/content/drive/MyDrive/BERT/sentiment_bert_model/classes.dict",
        "load_path": "/content/drive/MyDrive/BERT/sentiment_bert_model/classes.dict",
        "in": "y",
        "out": "y_ids"
      },
      {
        "class_name": "torch_transformers_preprocessor",
        "vocab_file": "/content/drive/MyDrive/BERT/rubert-base-cased-sentiment/",
        "do_lower_case": true,
        "max_seq_length": 512,
        "in": [
          "x"
        ],
        "out": [
          "bert_features"
        ]
      },
      {
        "in": "y_ids",
        "out": "y_onehot",
        "class_name": "one_hotter",
        "depth": "#classes_vocab.len",
        "single_vector": true
      },
      {
        "class_name": "torch_transformers_classifier",
        "n_classes": 3,
        "return_probas": true,
        "pretrained_bert": "/content/drive/MyDrive/BERT/rubert-base-cased-sentiment/",
        "save_path": "/content/drive/MyDrive/BERT/sentiment_bert_model/model",
        "load_path": "/content/drive/MyDrive/BERT/sentiment_bert_model/model",
        "optimizer": "AdamW",
        "optimizer_parameters": {
          "lr": 1e-05
        },
        "learning_rate_drop_patience": 5,
        "learning_rate_drop_div": 2.0,
        "in": [
          "bert_features"
        ],
        "in_y": [
          "y_ids"
        ],
        "out": [
          "y_pred_probas"
        ]
      },
      {
        "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": 5,
    "batch_size": 8,
    "metrics": [
      "accuracy",
      "f1_macro",
      "f1_weighted",
      {
        "name": "roc_auc",
        "inputs": [
          "y_onehot",
          "y_pred_probas"
        ]
      }
    ],
    "validation_patience": 2,
    "val_every_n_epochs": 1,
    "log_every_n_epochs": 1,
    "show_examples": false,
    "evaluation_targets": [
      "train",
      "valid"
    ],
    "class_name": "nn_trainer"
  }
}