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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: namwoo/distilbert-base-uncased-finetuned-ner
    results: []

namwoo/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: 0.0339
  • Validation Loss: 0.0623
  • Train Precision: 0.9239
  • Train Recall: 0.9335
  • Train F1: 0.9287
  • 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': {'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
0.1982 0.0715 0.9040 0.9218 0.9128 0.9799 0
0.0537 0.0618 0.9202 0.9305 0.9254 0.9827 1
0.0339 0.0623 0.9239 0.9335 0.9287 0.9829 2

Framework versions

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