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bert-model-english

This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.1408
  • Train Sparse Categorical Accuracy: 0.9512
  • Validation Loss: nan
  • Validation Sparse Categorical Accuracy: 0.0
  • Epoch: 4

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:

  • optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Sparse Categorical Accuracy Validation Loss Validation Sparse Categorical Accuracy Epoch
0.2775 0.8887 nan 0.0 0
0.1702 0.9390 nan 0.0 1
0.1300 0.9555 nan 0.0 2
0.1346 0.9544 nan 0.0 3
0.1408 0.9512 nan 0.0 4

Framework versions

  • Transformers 4.16.2
  • TensorFlow 2.7.0
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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