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bertimbau-base-lener-br-finetuned-lener-br

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bertimbau-base-lener-br-finetuned-lener-br / README.md
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Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#4)
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metadata
language:
  - pt
license: mit
tags:
  - generated_from_trainer
datasets:
  - lener_br
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: bertimbau-base-lener-br-finetuned-lener-br
    results:
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: lener_br
          type: lener_br
          config: lener_br
          split: train
          args: lener_br
        metrics:
          - type: precision
            value: 0.8942967409948542
            name: Precision
          - type: recall
            value: 0.8969892473118279
            name: Recall
          - type: f1
            value: 0.8956409705819198
            name: F1
          - type: accuracy
            value: 0.9696009264479559
            name: Accuracy
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: lener_br
          type: lener_br
          config: lener_br
          split: test
        metrics:
          - type: accuracy
            value: 0.981178408105048
            name: Accuracy
            verified: true
            verifyToken: >-
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          - type: precision
            value: 0.98709417546121
            name: Precision
            verified: true
            verifyToken: >-
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          - type: recall
            value: 0.9862996055703132
            name: Recall
            verified: true
            verifyToken: >-
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          - type: f1
            value: 0.986696730552424
            name: F1
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.144147127866745
            name: loss
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmM1ZDE5N2EyZGEyYzYzMmZjZDllZDhmYTgxNjIzODFhN2M2M2IyNWI3Y2IyMDdhOTkzZDA1MTE5NjkyODRlNiIsInZlcnNpb24iOjF9.L_Au7zxnzAtLRljLdlcFL1E-RWlmHty5W4YDMay9wH_PNZaI0X2MK5ifYP0871GHjAcmtk2M_Q-wIW7tHn0KAQ
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: lener_br
          type: lener_br
          config: lener_br
          split: validation
        metrics:
          - type: accuracy
            value: 0.9696009264479559
            name: Accuracy
            verified: true
            verifyToken: >-
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          - type: precision
            value: 0.974166236103935
            name: Precision
            verified: true
            verifyToken: >-
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          - type: recall
            value: 0.9847359110437199
            name: Recall
            verified: true
            verifyToken: >-
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          - type: f1
            value: 0.9794225581044623
            name: F1
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.26272761821746826
            name: loss
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzE4NmEzMjZlYmM1MzlkNzk5ZDE1M2IzYzNlNmM4YjgwNjRhZGVkZTFmNTBhZTVmOWEyZTVhNGM2MDljZjc2NSIsInZlcnNpb24iOjF9.xt17F4zNWnhlkLrjQv9tcl9ZeY68kr5UKCJhb8dDkwPIGS2u4ojyK8QtbKXO-_QY-X_oQZgdlbvQX4QYVVC4DQ

bertimbau-base-lener-br-finetuned-lener-br

This model is a fine-tuned version of Luciano/bertimbau-base-finetuned-lener-br on the lener_br dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Precision: 0.8943
  • Recall: 0.8970
  • F1: 0.8956
  • Accuracy: 0.9696

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
0.0678 1.0 1957 nan 0.8148 0.8882 0.8499 0.9689
0.0371 2.0 3914 nan 0.8347 0.9022 0.8671 0.9671
0.0242 3.0 5871 nan 0.8491 0.8905 0.8693 0.9716
0.0197 4.0 7828 nan 0.9014 0.8772 0.8892 0.9780
0.0135 5.0 9785 nan 0.8651 0.9060 0.8851 0.9765
0.013 6.0 11742 nan 0.8882 0.9054 0.8967 0.9767
0.0084 7.0 13699 nan 0.8559 0.9097 0.8820 0.9751
0.0069 8.0 15656 nan 0.8916 0.8828 0.8872 0.9696
0.0047 9.0 17613 nan 0.8964 0.8931 0.8948 0.9716
0.0028 10.0 19570 nan 0.8864 0.9047 0.8955 0.9691
0.0023 11.0 21527 nan 0.8860 0.9011 0.8935 0.9693
0.0009 12.0 23484 nan 0.8952 0.8987 0.8970 0.9686
0.0014 13.0 25441 nan 0.8929 0.8985 0.8957 0.9699
0.0025 14.0 27398 nan 0.8914 0.8981 0.8947 0.9700
0.001 15.0 29355 nan 0.8943 0.8970 0.8956 0.9696

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1