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vesteinn
/
ScandiBERT-NER

Token Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Inference Endpoints
Model card Files Community
1
ScandiBERT-NER
File size: 1,469 Bytes 
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{
  "_name_or_path": "vesteinn/ScandiBERT",
  "architectures": [
    "XLMRobertaForTokenClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "bos_token_id": 0,
  "classifier_dropout": null,
  "eos_token_id": 2,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "id2label": {
   "0": "O",
    "1": "B-Date",
    "2": "B-Location",
    "3": "B-Miscellaneous",
    "4": "B-Money",
    "5": "B-Organization",
    "6": "B-Percent",
    "7": "B-Person",
    "8": "B-Time",
    "9": "I-Date",
    "10": "I-Location",
    "11": "I-Miscellaneous",
    "12": "I-Money",
    "13": "I-Organization",
    "14": "I-Percent",
    "15": "I-Person",
    "16": "I-Time"
  },
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "label2id": {
   "LABEL_0": 0,
    "LABEL_1": 1,
    "LABEL_10": 10,
    "LABEL_11": 11,
    "LABEL_12": 12,
    "LABEL_13": 13,
    "LABEL_14": 14,
    "LABEL_15": 15,
    "LABEL_16": 16,
    "LABEL_2": 2,
    "LABEL_3": 3,
    "LABEL_4": 4,
    "LABEL_5": 5,
    "LABEL_6": 6,
    "LABEL_7": 7,
    "LABEL_8": 8,
    "LABEL_9": 9
  },
  "layer_norm_eps": 1e-05,
  "max_position_embeddings": 514,
  "model_type": "xlm-roberta",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 1,
  "position_embedding_type": "absolute",
  "torch_dtype": "float32",
  "transformers_version": "4.15.0",
  "type_vocab_size": 1,
  "use_cache": true,
  "vocab_size": 50005
}