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goat923/my_awesome_wnut_model

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: 0.1165
  • Validation Loss: 0.2494
  • Train Precision: 0.6287
  • Train Recall: 0.4557
  • Train F1: 0.5284
  • Train Accuracy: 0.9482
  • 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': 636, '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
0.3527 0.3075 0.3319 0.0945 0.1471 0.9281 0
0.1583 0.2594 0.5886 0.4211 0.4909 0.9455 1
0.1165 0.2494 0.6287 0.4557 0.5284 0.9482 2

Framework versions

  • Transformers 4.32.1
  • TensorFlow 2.12.0
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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