--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: tunarebus/distilbert-base-uncased-finetuned-imdb results: [] --- # tunarebus/distilbert-base-uncased-finetuned-imdb 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: 2.3941 - Validation Loss: 2.4019 - Epoch: 19 ## 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': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -949, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: mixed_float16 ### Training results | Train Loss | Validation Loss | Epoch | |:----------:|:---------------:|:-----:| | 2.3668 | 2.3869 | 0 | | 2.4055 | 2.3907 | 1 | | 2.3880 | 2.3301 | 2 | | 2.3677 | 2.4133 | 3 | | 2.3891 | 2.4048 | 4 | | 2.3861 | 2.4312 | 5 | | 2.4031 | 2.3794 | 6 | | 2.3730 | 2.3708 | 7 | | 2.4306 | 2.3910 | 8 | | 2.4102 | 2.3748 | 9 | | 2.4285 | 2.4060 | 10 | | 2.4150 | 2.4133 | 11 | | 2.3953 | 2.4465 | 12 | | 2.4173 | 2.3387 | 13 | | 2.3997 | 2.3561 | 14 | | 2.4091 | 2.4217 | 15 | | 2.4050 | 2.3832 | 16 | | 2.4103 | 2.4008 | 17 | | 2.4019 | 2.3851 | 18 | | 2.3941 | 2.4019 | 19 | ### Framework versions - Transformers 4.35.2 - TensorFlow 2.14.0 - Datasets 2.15.0 - Tokenizers 0.15.0