--- license: apache-2.0 base_model: distilroberta-base tags: - generated_from_keras_callback model-index: - name: pippinnie/distilroberta-base-finetuned-cyber-readme-v2 results: [] --- # pippinnie/distilroberta-base-finetuned-cyber-readme-v2 This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 2.5523 - Train Accuracy: 0.0844 - Validation Loss: 2.2331 - Validation Accuracy: 0.0916 - 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| | 2.9763 | 0.0766 | 2.5856 | 0.0839 | 0 | | 2.8159 | 0.0795 | 2.4501 | 0.0871 | 1 | | 2.7022 | 0.0816 | 2.3638 | 0.0892 | 2 | | 2.6160 | 0.0831 | 2.2778 | 0.0909 | 3 | | 2.5523 | 0.0844 | 2.2331 | 0.0916 | 4 | ### Framework versions - Transformers 4.38.2 - TensorFlow 2.16.1 - Datasets 2.18.0 - Tokenizers 0.15.2