--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_keras_callback model-index: - name: ac-01-bert-finetuned results: [] --- # ac-01-bert-finetuned This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.1172 - Validation Loss: 0.5493 - Train F1: 0.8137 - Epoch: 4 ## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 4030, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} - training_precision: float32 ### Training results | Train Loss | Validation Loss | Train F1 | Epoch | |:----------:|:---------------:|:--------:|:-----:| | 0.5556 | 0.4472 | 0.7965 | 0 | | 0.3877 | 0.4268 | 0.8107 | 1 | | 0.2931 | 0.4459 | 0.8165 | 2 | | 0.1734 | 0.5071 | 0.8223 | 3 | | 0.1172 | 0.5493 | 0.8137 | 4 | ### Framework versions - Transformers 4.31.0 - TensorFlow 2.13.0 - Datasets 2.14.4 - Tokenizers 0.13.3