Transformer-DeID: Deidentification of free-text clinical notes with transformers 1.0.0

File: <base>/transformer_models/bert_model_100/config.json (983 bytes)
{
  "_name_or_path": "bert-base-cased",
  "architectures": [
    "BertForTokenClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "id2label": {
    "0": "O",
    "1": "AGE",
    "2": "CONTACT",
    "3": "DATE",
    "4": "ID",
    "5": "LOCATION",
    "6": "NAME",
    "7": "PROFESSION"
  },
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "label2id": {
    "AGE": 1,
    "CONTACT": 2,
    "DATE": 3,
    "ID": 4,
    "LOCATION": 5,
    "NAME": 6,
    "O": 0,
    "PROFESSION": 7
  },
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 0,
  "position_embedding_type": "absolute",
  "torch_dtype": "float32",
  "transformers_version": "4.21.2",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 28996
}