ClinicalNER / config.json
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{
"_name_or_path": "xlm-roberta-base",
"architectures": [
"XLMRobertaForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"classifier_dropout": null,
"eos_token_id": 2,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "O",
"1": "B-Drug",
"2": "I-Drug",
"3": "B-Form",
"4": "I-Form",
"5": "B-Strength",
"6": "I-Strength",
"7": "B-Frequency",
"8": "I-Frequency",
"9": "B-Dosage",
"10": "I-Dosage",
"11": "B-Duration",
"12": "I-Duration"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"label2id": {
"B-Dosage": 9,
"B-Drug": 1,
"B-Duration": 11,
"B-Form": 3,
"B-Frequency": 7,
"B-Strength": 5,
"I-Dosage": 10,
"I-Drug": 2,
"I-Duration": 12,
"I-Form": 4,
"I-Frequency": 8,
"I-Strength": 6,
"O": 0
},
"layer_norm_eps": 1e-05,
"max_position_embeddings": 514,
"model_type": "xlm-roberta",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"output_past": true,
"pad_token_id": 1,
"position_embedding_type": "absolute",
"torch_dtype": "float32",
"transformers_version": "4.20.1",
"type_vocab_size": 1,
"use_cache": true,
"vocab_size": 250002
}