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bhattronak/my-awesome-address-tokenizer-model-v13-50k

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: 0.1109
  • Validation Loss: 0.1177
  • Train Precision: 0.9320
  • Train Recall: 0.9481
  • Train F1: 0.9400
  • Train Accuracy: 0.9584
  • Epoch: 1

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': 4720, '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
0.2053 0.1266 0.9223 0.9448 0.9334 0.9552 0
0.1109 0.1177 0.9320 0.9481 0.9400 0.9584 1

Framework versions

  • Transformers 4.35.0
  • TensorFlow 2.14.0
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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