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vladjr/bert_ner_tf_pln

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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vladjr/bertnertf_pln

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: 0.1067
  • —Validation Loss: 0.1824
  • —Train Precision: 0.8287
  • —Train Recall: 0.8193
  • —Train F1: 0.8240
  • —Train Accuracy: 0.9458
  • —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', 'learningrate': {'module': 'keras.optimizers.schedules', 'classname': 'PolynomialDecay', 'config': {'initiallearningrate': 2e-05, 'decaysteps': 4674, 'endlearningrate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registeredname': None}, 'decay': 0.0, 'beta1': 0.9, 'beta2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weightdecayrate': 0.01}
  • —training_precision: float32

Training results

Train LossValidation LossTrain PrecisionTrain RecallTrain F1Train AccuracyEpoch
0.18900.18110.82900.80530.81700.94450
0.12500.17390.82430.81880.82160.94571
0.10670.18240.82870.81930.82400.94582

Framework versions

  • —Transformers 4.35.2
  • —TensorFlow 2.14.0
  • —Datasets 2.15.0
  • —Tokenizers 0.15.0