--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: Tarkan/cikolata-finetuned-hastalik results: [] --- # Tarkan/cikolata-finetuned-hastalik 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: 0.1853 - Validation Loss: 0.0921 - Train Precision: 0.6410 - Train Recall: 0.7388 - Train F1: 0.6864 - Train Accuracy: 0.9686 - Epoch: 0 ## 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': 339, '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 | |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| | 0.1853 | 0.0921 | 0.6410 | 0.7388 | 0.6864 | 0.9686 | 0 | ### Framework versions - Transformers 4.21.0 - TensorFlow 2.8.2 - Datasets 2.4.0 - Tokenizers 0.12.1