--- license: apache-2.0 base_model: distilbert-base-cased tags: - generated_from_keras_callback model-index: - name: Ozgunn/distil_bert_pii_model-fine-tuned results: [] --- # Ozgunn/distil_bert_pii_model-fine-tuned This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0091 - Validation Loss: 0.0126 - Train Precision: 0.2666 - Train Recall: 0.4496 - Train F1: 0.3347 - Train Accuracy: 0.9967 - 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': 8154, '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 | |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| | 0.0332 | 0.0126 | 0.2666 | 0.4496 | 0.3347 | 0.9967 | 0 | | 0.0091 | 0.0126 | 0.2666 | 0.4496 | 0.3347 | 0.9967 | 1 | ### Framework versions - Transformers 4.38.2 - TensorFlow 2.15.0 - Datasets 2.18.0 - Tokenizers 0.15.2