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Felipe1908/bert-safety-monitor-balanced

sourceHugging Facemitupdated 10mo agoView on Hugging Face
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Model Card

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bert-safety-monitor-balanced

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: 0.5227
  • —Accuracy: 0.8558
  • —F1 Macro: 0.8384

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
  • —trainbatchsize: 16
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 8
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyF1 Macro
No log1.03550.34710.82570.8129
0.47982.07100.43870.79400.7977
0.29583.010650.47140.82880.8202
0.29584.014200.37270.84470.8293
0.23085.017750.43050.86210.8417
0.17416.021300.51890.85580.8384
0.17417.024850.45210.86050.8363
0.1638.028400.52270.85580.8384

Framework versions

  • —Transformers 4.57.2
  • —Pytorch 2.9.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.1