--- license: apache-2.0 base_model: bert-large-uncased tags: - generated_from_trainer metrics: - accuracy - precision - recall model-index: - name: phishing_4_1 results: [] --- # phishing_4_1 This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7542 - Accuracy: 0.9894 - Precision: 0.9916 - Recall: 0.9872 - False Positive Rate: 0.0084 ## 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: - learning_rate: 2e-05 - train_batch_size: 12 - eval_batch_size: 12 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | False Positive Rate | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:-------------------:| | 0.77 | 1.0 | 3025 | 0.7619 | 0.9818 | 0.9796 | 0.9841 | 0.0205 | | 0.7579 | 2.0 | 6050 | 0.7603 | 0.9834 | 0.9982 | 0.9685 | 0.0018 | | 0.7595 | 3.0 | 9075 | 0.7605 | 0.9831 | 0.9982 | 0.9680 | 0.0018 | | 0.7546 | 4.0 | 12100 | 0.7542 | 0.9894 | 0.9916 | 0.9872 | 0.0084 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.1.2 - Datasets 2.18.0 - Tokenizers 0.15.2