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End of training
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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: kasrahabib/distilbert-base-uncased-finetuned-re_smell_detector
    results: []

kasrahabib/distilbert-base-uncased-finetuned-re_smell_detector

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: 0.0045
  • Validation Loss: 0.0243
  • Train Precision: 95.87
  • Train Recall: 93.28
  • Train F1: 94.56
  • Train Accuracy: 100.0
  • 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': 4614, '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
0.0447 0.0386 92.96 88.65 90.75 99.0 0
0.0072 0.0289 92.36 91.65 92.0 99.0 1
0.0045 0.0243 95.87 93.28 94.56 100.0 2

Framework versions

  • Transformers 4.24.0
  • TensorFlow 2.9.2
  • Datasets 2.6.1
  • Tokenizers 0.13.1