--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: vladjr/my_awesome_wnut_model results: [] --- # vladjr/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: 0.1257 - Validation Loss: 0.2667 - Train Precision: 0.5476 - Train Recall: 0.3923 - Train F1: 0.4571 - Train Accuracy: 0.9438 - 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 636, '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 | |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| | 0.3497 | 0.3273 | 0.3151 | 0.0275 | 0.0506 | 0.9219 | 0 | | 0.1715 | 0.2791 | 0.4513 | 0.3050 | 0.3640 | 0.9385 | 1 | | 0.1257 | 0.2667 | 0.5476 | 0.3923 | 0.4571 | 0.9438 | 2 | ### Framework versions - Transformers 4.35.2 - TensorFlow 2.14.0 - Datasets 2.15.0 - Tokenizers 0.15.0