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Thrisulk/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: 0.0353
  • Validation Loss: 0.0596
  • Train Precision: 0.9199
  • Train Recall: 0.9337
  • Train F1: 0.9267
  • Train Accuracy: 0.9829
  • 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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
0.2022 0.0724 0.9070 0.9161 0.9115 0.9795 0
0.0563 0.0615 0.9181 0.9304 0.9242 0.9821 1
0.0353 0.0596 0.9199 0.9337 0.9267 0.9829 2

Framework versions

  • Transformers 4.41.1
  • TensorFlow 2.15.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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