bert-finetuned-mrpc / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: bert-finetuned-mrpc
    results: []

bert-finetuned-mrpc

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: 0.1719
  • Train Accuracy: 0.9359
  • Validation Loss: 0.4050
  • Validation Accuracy: 0.8382
  • 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1374, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Accuracy Validation Loss Validation Accuracy Epoch
0.5877 0.6823 0.4665 0.8015 0
0.3843 0.8201 0.4026 0.8309 1
0.1719 0.9359 0.4050 0.8382 2

Framework versions

  • Transformers 4.19.1
  • TensorFlow 2.8.0
  • Datasets 2.2.1
  • Tokenizers 0.12.1