bertimbau-large-lener_br

This model is a fine-tuned version of neuralmind/bert-large-portuguese-cased on the lener_br dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1271
  • Precision: 0.8965
  • Recall: 0.9198
  • F1: 0.9080
  • Accuracy: 0.9801

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0674 1.0 1957 0.1349 0.7617 0.8710 0.8127 0.9594
0.0443 2.0 3914 0.1867 0.6862 0.9194 0.7858 0.9575
0.0283 3.0 5871 0.1185 0.8206 0.8766 0.8477 0.9678
0.0226 4.0 7828 0.1405 0.8072 0.8978 0.8501 0.9708
0.0141 5.0 9785 0.1898 0.7224 0.9194 0.8090 0.9629
0.01 6.0 11742 0.1655 0.9062 0.8856 0.8958 0.9741
0.012 7.0 13699 0.1271 0.8965 0.9198 0.9080 0.9801
0.0091 8.0 15656 0.1919 0.8890 0.8886 0.8888 0.9719
0.0042 9.0 17613 0.1725 0.8977 0.8985 0.8981 0.9744
0.0043 10.0 19570 0.1530 0.8878 0.9034 0.8955 0.9761
0.0042 11.0 21527 0.1635 0.8792 0.9108 0.8947 0.9774
0.0033 12.0 23484 0.2009 0.8155 0.9138 0.8619 0.9719
0.0008 13.0 25441 0.1766 0.8737 0.9135 0.8932 0.9755
0.0005 14.0 27398 0.1868 0.8616 0.9129 0.8865 0.9743
0.0014 15.0 29355 0.1910 0.8694 0.9101 0.8893 0.9746

Framework versions

  • Transformers 4.8.2
  • Pytorch 1.9.0+cu102
  • Datasets 1.9.0
  • Tokenizers 0.10.3
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