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notmaineyy/distilbert-base-uncased-finetuned-ner

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

  • Train Loss: 0.0344
  • Validation Loss: 0.0633
  • Train Precision: 0.9181
  • Train Recall: 0.9322
  • Train F1: 0.9251
  • Train Accuracy: 0.9823
  • 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, '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 Train Precision Train Recall Train F1 Train Accuracy Epoch
0.2048 0.0749 0.8898 0.9129 0.9012 0.9784 0
0.0556 0.0621 0.9150 0.9300 0.9224 0.9819 1
0.0344 0.0633 0.9181 0.9322 0.9251 0.9823 2

Framework versions

  • Transformers 4.20.1
  • TensorFlow 2.8.2
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Inference API
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