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U4RASD
/
TypePredictor

Text Classification
PyTorch
Arabic
type_predictor
arabic
named-entity-recognition
entity-typing
wojood
neoarabert
mention-classification
Model card Files
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 Community
TypePredictor
File size: 1,709 Bytes
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{
  "architecture": "NeoAraBERTTypePredictor",
  "task": "mention-level 21-class Arabic entity typing",
  "base_model": "U4RASD/NeoAraBERT",
  "input_markers": [
    "[ENT]",
    "[/ENT]"
  ],
  "representation": "last hidden state at token position 0 (CLS)",
  "dropout": 0.1,
  "classifier": [
    768,
    21
  ],
  "loss": "ordinary unweighted multiclass cross-entropy",
  "num_labels": 21,
  "labels": [
    "GPE",
    "ORG",
    "DATE",
    "PERS",
    "NORP",
    "ORDINAL",
    "OCC",
    "EVENT",
    "CARDINAL",
    "LOC",
    "WEBSITE",
    "FAC",
    "LAW",
    "TIME",
    "MONEY",
    "CURR",
    "LANGUAGE",
    "PERCENT",
    "PRODUCT",
    "QUANTITY",
    "UNIT"
  ],
  "tokenizer_size": 65002,
  "hidden_size": 768,
  "max_length": 512,
  "context_candidates": [
    null,
    500,
    300,
    150,
    80,
    30,
    0
  ],
  "architectures": [
    "NeoAraBERTTypePredictor"
  ],
  "model_type": "type_predictor",
  "id2label": {
    "0": "GPE",
    "1": "ORG",
    "2": "DATE",
    "3": "PERS",
    "4": "NORP",
    "5": "ORDINAL",
    "6": "OCC",
    "7": "EVENT",
    "8": "CARDINAL",
    "9": "LOC",
    "10": "WEBSITE",
    "11": "FAC",
    "12": "LAW",
    "13": "TIME",
    "14": "MONEY",
    "15": "CURR",
    "16": "LANGUAGE",
    "17": "PERCENT",
    "18": "PRODUCT",
    "19": "QUANTITY",
    "20": "UNIT"
  },
  "label2id": {
    "GPE": 0,
    "ORG": 1,
    "DATE": 2,
    "PERS": 3,
    "NORP": 4,
    "ORDINAL": 5,
    "OCC": 6,
    "EVENT": 7,
    "CARDINAL": 8,
    "LOC": 9,
    "WEBSITE": 10,
    "FAC": 11,
    "LAW": 12,
    "TIME": 13,
    "MONEY": 14,
    "CURR": 15,
    "LANGUAGE": 16,
    "PERCENT": 17,
    "PRODUCT": 18,
    "QUANTITY": 19,
    "UNIT": 20
  }
}