bert-ner-test-1 / README.md
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metadata
license: apache-2.0
base_model: bert-base-cased
tags:
  - generated_from_keras_callback
model-index:
  - name: chosenone80/bert-ner-test-1
    results: []

chosenone80/bert-ner-test-1

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: 0.1319
  • Validation Loss: 0.0479
  • Train Precision: 0.9163
  • Train Recall: 0.9298
  • Train F1: 0.9230
  • Train Accuracy: 0.9874
  • Epoch: 0

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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 877, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Precision Train Recall Train F1 Train Accuracy Epoch
0.1319 0.0479 0.9163 0.9298 0.9230 0.9874 0

Framework versions

  • Transformers 4.35.2
  • TensorFlow 2.15.0
  • Datasets 2.17.1
  • Tokenizers 0.15.2