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BRlkl/BingoGuard-bert-base-portuguese-cased-benchmarks

sourceHugging Faceupdated 1y agoView on Hugging Face
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BingoGuard-bert-base-portuguese-cased-benchmarks

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.9060
  • —Accuracy: 0.8064
  • —F1: 0.7928

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: 5e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 64
  • —optimizer: Use adamwtorchfused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 8

Training results

Training LossEpochStepValidation LossAccuracyF1
0.39791.08560.38140.83430.8385
0.3262.017120.38880.83380.8314
0.26313.025680.46250.83150.8279
0.23214.034240.47110.82500.8210
0.20485.042800.53470.82310.8194
0.17316.051360.61650.81510.8051
0.1437.059920.77260.80640.7914
0.09638.068480.90600.80640.7928

Framework versions

  • —Transformers 4.55.4
  • —Pytorch 2.8.0+cu128
  • —Datasets 3.6.0
  • —Tokenizers 0.21.4