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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: phishing_detection_fine_tuned_bert |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# phishing_detection_fine_tuned_bert |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3343 |
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- Accuracy: 0.8565 |
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- F1: 0.8573 |
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- Precision: 0.8596 |
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- Recall: 0.8565 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.411 | 1.0 | 3622 | 0.3300 | 0.8222 | 0.8242 | 0.8509 | 0.8222 | |
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| 0.4471 | 2.0 | 7244 | 0.6779 | 0.8154 | 0.8067 | 0.8274 | 0.8154 | |
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| 0.6583 | 3.0 | 10866 | 0.6717 | 0.6079 | 0.4597 | 0.3695 | 0.6079 | |
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| 0.6286 | 4.0 | 14488 | 0.6698 | 0.6079 | 0.4597 | 0.3695 | 0.6079 | |
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| 0.6527 | 5.0 | 18110 | 0.6697 | 0.6079 | 0.4597 | 0.3695 | 0.6079 | |
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| 0.336 | 6.0 | 21732 | 0.4681 | 0.7707 | 0.7719 | 0.8293 | 0.7707 | |
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| 0.5686 | 7.0 | 25354 | 0.6242 | 0.5740 | 0.5518 | 0.7128 | 0.5740 | |
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| 0.334 | 8.0 | 28976 | 0.3666 | 0.8279 | 0.8298 | 0.8433 | 0.8279 | |
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| 0.4017 | 9.0 | 32598 | 0.3711 | 0.8571 | 0.8561 | 0.8564 | 0.8571 | |
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| 0.2285 | 10.0 | 36220 | 0.3343 | 0.8565 | 0.8573 | 0.8596 | 0.8565 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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