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fintuned-bert-disfluency

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

  • Train Loss: 0.0814
  • Train Sparse Categorical Accuracy: 0.9795
  • Validation Loss: 0.0816
  • Validation Sparse Categorical Accuracy: 0.9795
  • Epoch: 2

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
0.1105 0.9694 0.0821 0.9800 0
0.0942 0.9759 0.0987 0.9765 1
0.0814 0.9795 0.0816 0.9795 2

Framework versions

  • Transformers 4.21.3
  • TensorFlow 2.8.2
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Dataset used to train kapilchauhan/fintuned-bert-disfluency

Evaluation results