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priyanshug0405/my_awesome_wnut_model_2

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: 0.0378
  • Validation Loss: 0.0597
  • Train Precision: 0.9157
  • Train Recall: 0.9151
  • Train F1: 0.9154
  • Train Accuracy: 0.9807
  • 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': 11250, '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
0.1337 0.0709 0.8861 0.8913 0.8887 0.9753 0
0.0562 0.0600 0.9113 0.9107 0.9110 0.9795 1
0.0378 0.0597 0.9157 0.9151 0.9154 0.9807 2

Framework versions

  • Transformers 4.37.0
  • TensorFlow 2.15.0
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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