--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: kunxiaogao/my_awesome_wnut_model results: [] --- # kunxiaogao/my_awesome_wnut_model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.1293 - Validation Loss: 0.2770 - Train Precision: 0.5634 - Train Recall: 0.3828 - Train F1: 0.4558 - Train Accuracy: 0.9435 - 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 | |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| | 0.3690 | 0.3318 | 0.4888 | 0.1304 | 0.2059 | 0.9299 | 0 | | 0.1706 | 0.2808 | 0.5269 | 0.3278 | 0.4041 | 0.9409 | 1 | | 0.1293 | 0.2770 | 0.5634 | 0.3828 | 0.4558 | 0.9435 | 2 | ### Framework versions - Transformers 4.26.0 - TensorFlow 2.9.2 - Datasets 2.9.0 - Tokenizers 0.13.2