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mrm8488
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biomedtra-small-finenuned-clinical-ner

Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
Spanish
electra
clinical
pii
ner
medical
Inference Endpoints
Model card Files Metrics Community
1
mrm8488 commited on
Commit
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1 Parent(s): a8d5dca

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Files changed (10) hide show
  1. config.json +80 -0
  2. eval_results.txt +9 -0
  3. pytorch_model.bin +3 -0
  4. runs/Feb26_20-26-36_0ec3306a6e7b/1645907245.9118726/events.out.tfevents.1645907245.0ec3306a6e7b.461.1 +3 -0
  5. runs/Feb26_20-26-36_0ec3306a6e7b/events.out.tfevents.1645907245.0ec3306a6e7b.461.0 +3 -0
  6. runs/Feb26_20-26-36_0ec3306a6e7b/events.out.tfevents.1645907976.0ec3306a6e7b.461.2 +3 -0
  7. special_tokens_map.json +1 -0
  8. tokenizer_config.json +1 -0
  9. training_args.bin +3 -0
  10. vocab.txt +0 -0
config.json ADDED
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+ {
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+ "_name_or_path": "mrm8488/biomedtra-small-es",
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+ "architectures": [
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+ "ElectraForTokenClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "embedding_size": 128,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 256,
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+ "id2label": {
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+ "0": "",
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+ "1": "CALLE",
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+ "2": "CENTRO_SALUD",
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+ "3": "CORREO_ELECTRONICO",
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+ "4": "EDAD_SUJETO_ASISTENCIA",
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+ "5": "FAMILIARES_SUJETO_ASISTENCIA",
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+ "6": "FECHAS",
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+ "7": "HOSPITAL",
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+ "8": "ID_ASEGURAMIENTO",
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+ "9": "ID_CONTACTO_ASISTENCIAL",
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+ "10": "ID_SUJETO_ASISTENCIA",
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+ "11": "ID_TITULACION_PERSONAL_SANITARIO",
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+ "12": "INSTITUCION",
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+ "13": "NOMBRE_PERSONAL_SANITARIO",
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+ "14": "NOMBRE_SUJETO_ASISTENCIA",
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+ "15": "NUMERO_FAX",
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+ "16": "NUMERO_TELEFONO",
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+ "17": "O",
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+ "18": "OTROS_SUJETO_ASISTENCIA",
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+ "19": "PAIS",
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+ "20": "PROFESION",
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+ "21": "SEXO_SUJETO_ASISTENCIA",
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+ "22": "TERRITORIO"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 1024,
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+ "label2id": {
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+ "": 0,
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+ "CALLE": 1,
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+ "CENTRO_SALUD": 2,
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+ "CORREO_ELECTRONICO": 3,
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+ "EDAD_SUJETO_ASISTENCIA": 4,
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+ "FAMILIARES_SUJETO_ASISTENCIA": 5,
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+ "FECHAS": 6,
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+ "HOSPITAL": 7,
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+ "ID_ASEGURAMIENTO": 8,
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+ "ID_CONTACTO_ASISTENCIAL": 9,
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+ "ID_SUJETO_ASISTENCIA": 10,
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+ "ID_TITULACION_PERSONAL_SANITARIO": 11,
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+ "INSTITUCION": 12,
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+ "NOMBRE_PERSONAL_SANITARIO": 13,
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+ "NOMBRE_SUJETO_ASISTENCIA": 14,
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+ "NUMERO_FAX": 15,
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+ "NUMERO_TELEFONO": 16,
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+ "O": 17,
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+ "OTROS_SUJETO_ASISTENCIA": 18,
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+ "PAIS": 19,
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+ "PROFESION": 20,
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+ "SEXO_SUJETO_ASISTENCIA": 21,
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+ "TERRITORIO": 22
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "electra",
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+ "num_attention_heads": 4,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "summary_activation": "gelu",
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+ "summary_last_dropout": 0.1,
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+ "summary_type": "first",
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+ "summary_use_proj": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.17.0.dev0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 31002
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+ }
eval_results.txt ADDED
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+ eval_loss = 0.17097021639347076
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+ eval_accuracy_score = 0.9747292075155622
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+ eval_precision = 0.6711051930758988
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+ eval_recall = 0.6480925846549507
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+ eval_f1 = 0.6593981683384212
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+ eval_runtime = 6.171
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+ eval_samples_per_second = 258.629
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+ eval_steps_per_second = 8.102
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+ epoch = 64.0
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special_tokens_map.json ADDED
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tokenizer_config.json ADDED
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vocab.txt ADDED
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