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

MUmairAB/bert-ner

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: 0.0003
  • Validation Loss: 0.0880
  • Epoch: 18

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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 17560, '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-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Epoch
0.1775 0.0635 0
0.0470 0.0559 1
0.0278 0.0603 2
0.0174 0.0603 3
0.0124 0.0615 4
0.0077 0.0722 5
0.0060 0.0731 6
0.0038 0.0757 7
0.0043 0.0731 8
0.0041 0.0735 9
0.0019 0.0724 10
0.0019 0.0786 11
0.0010 0.0843 12
0.0008 0.0814 13
0.0011 0.0867 14
0.0008 0.0883 15
0.0005 0.0861 16
0.0005 0.0869 17
0.0003 0.0880 18

Framework versions

  • Transformers 4.30.2
  • TensorFlow 2.12.0
  • Datasets 2.13.1
  • Tokenizers 0.13.3