pucpr-br/tempclin-biobertpt-bio

Portuguese NER- TempClinBr - BioBERTpt(bio)

Treinado com BioBERTpt(bio), com o corpus TempClinBr.

Metricas:

        precision    recall  f1-score   support

           0       0.44      0.29      0.35        28
           1       0.75      0.60      0.66       420
           2       0.57      0.40      0.47        10
           3       0.57      0.36      0.44        11
           4       0.70      0.85      0.77       124
           5       0.72      0.67      0.69       291
           6       0.84      0.90      0.87      2236
           7       0.78      0.77      0.77       112
           8       0.85      0.75      0.80       503
           9       0.64      0.56      0.60        78
          10       0.81      0.82      0.81        71
          11       0.82      1.00      0.90        33

    accuracy                           0.81      3917
   macro avg       0.71      0.66      0.68      3917
weighted avg       0.81      0.81      0.80      3917

Parâmetros:

device = cuda (Colab)
nclasses = len(tag2id)
nepochs = 50 => parou na 16
batch_size = 16
batch_status = 32
learning_rate = 3e-5

early_stop = 5
max_length = 256
write_path = 'model'

Eval no conjunto de teste - TempClinBr OBS: Avaliação com tag "O" (label 7), se necessário fazer a média sem essa tag.

tag2id ={'I-Ocorrencia': 0,
 'I-Problema': 1,
 'I-DepartamentoClinico': 2,
 'B-DepartamentoClinico': 3,
 'B-Ocorrencia': 4,
 'B-Tratamento': 5,
 'O': 6,
 'B-Teste': 7,
 'B-Problema': 8,
 'I-Tratamento': 9,
 'B-Evidencia': 10,
 'I-Teste': 11,
 '<pad>': 12}

              precision    recall  f1-score   support

           0       0.59      0.20      0.29        51
           1       0.77      0.69      0.73       645
           2       0.67      0.71      0.69        14
           3       0.87      0.43      0.58        30
           4       0.71      0.80      0.75       146
           5       0.79      0.77      0.78       261
           6       0.84      0.93      0.88      2431
           7       0.80      0.66      0.73       194
           8       0.87      0.83      0.85       713
           9       0.83      0.62      0.71       146
          10       0.98      0.91      0.94       128
          11       0.54      0.21      0.30        99

    accuracy                           0.83      4858
   macro avg       0.77      0.65      0.69      4858
weighted avg       0.82      0.83      0.82      4858

Como citar: em breve