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NER_for_Chinese_Address

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NER_for_Chinese_Address
File size: 1,865 Bytes 
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{
  "bert_dir": "./model_hub/chinese-bert-wwm-ext/",
  "output_dir": "./checkpoint/cluener",
  "data_dir": "./data/",
  "data_path": "./data/cluener/ner_data",
  "labels": [
    "address",
    "book",
    "company",
    "game",
    "government",
    "movie",
    "name",
    "organization",
    "position",
    "scene"
  ],
  "bio_labels": [
    "O",
    "B-address",
    "I-address",
    "B-book",
    "I-book",
    "B-company",
    "I-company",
    "B-game",
    "I-game",
    "B-government",
    "I-government",
    "B-movie",
    "I-movie",
    "B-name",
    "I-name",
    "B-organization",
    "I-organization",
    "B-position",
    "I-position",
    "B-scene",
    "I-scene"
  ],
  "num_labels": 21,
  "label2id": {
    "O": 0,
    "B-address": 1,
    "I-address": 2,
    "B-book": 3,
    "I-book": 4,
    "B-company": 5,
    "I-company": 6,
    "B-game": 7,
    "I-game": 8,
    "B-government": 9,
    "I-government": 10,
    "B-movie": 11,
    "I-movie": 12,
    "B-name": 13,
    "I-name": 14,
    "B-organization": 15,
    "I-organization": 16,
    "B-position": 17,
    "I-position": 18,
    "B-scene": 19,
    "I-scene": 20
  },
  "id2label": {
    "0": "O",
    "1": "B-address",
    "2": "I-address",
    "3": "B-book",
    "4": "I-book",
    "5": "B-company",
    "6": "I-company",
    "7": "B-game",
    "8": "I-game",
    "9": "B-government",
    "10": "I-government",
    "11": "B-movie",
    "12": "I-movie",
    "13": "B-name",
    "14": "I-name",
    "15": "B-organization",
    "16": "I-organization",
    "17": "B-position",
    "18": "I-position",
    "19": "B-scene",
    "20": "I-scene"
  },
  "max_seq_len": 512,
  "epochs": 3,
  "train_batch_size": 12,
  "dev_batch_size": 12,
  "bert_learning_rate": 3e-05,
  "crf_learning_rate": 0.003,
  "adam_epsilon": 1e-08,
  "weight_decay": 0.01,
  "warmup_proportion": 0.01,
  "save_step": 500
}