--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: MALWARE-URL-DETECT results: [] --- # MALWARE-URL-DETECT With this model, it detects harmful links created to harm people such as phishing in Turkey. Classifies url addresses as malware and benign. Type the domain name of the url address in the text field for classification in API: Like this: "huggingface.com" To test the model, visit [USOM](https://www.usom.gov.tr/adres). Harmful links used in Turkey are shared up-to-date on this site. This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2122 - Accuracy: 0.945 - Precision: 0.9611 - Recall: 0.9287 - F1: 0.9446 ## 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: 5e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | No log | 1.0 | 63 | 0.2153 | 0.921 | 0.9953 | 0.8475 | 0.9155 | | No log | 2.0 | 126 | 0.1927 | 0.946 | 0.9669 | 0.9248 | 0.9453 | | No log | 3.0 | 189 | 0.2122 | 0.945 | 0.9611 | 0.9287 | 0.9446 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3