codebert base Malicious URLs This model is a fine tuned version of microsoft/codebert base. It achieves the following results on the evaluation set: Loss: 0.8225 Accuracy: 0.7279 Weighted f1: 0.6508 Micro f1: 0.7279 Macro f1: 0.4611 Weighted recall: 0.7279 Micro recall: 0.7279 Macro recall: 0.4422 Weighted precision: 0.6256 Micro precision: 0.7279 Macro precision: 0.5436 Model description For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP Projects/blob/main/Multiclass%20Classification/Malicious%20URLs/Malicious%20URLs%20 %20CodeBERT.ipynb Intended uses & limitations This model is intended to demonstrate my ability to solve a complex problem using technology. Training and evaluation data Dataset Source: https://www.kaggle.com/datasets/sid321axn/malicious urls dataset Input Word Length: Input Word Length By Class: Class Distribution: /Images/Class%20Distribution.png) Training procedure Training hyperparameters The following hyperparameters were used during training: learning rate: 2e 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:…
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