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--- |
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license: apache-2.0 |
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base_model: bert-large-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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- precision |
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- recall |
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model-index: |
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- name: toan_phishing |
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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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# toan_phishing |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3307 |
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- Accuracy: 0.9825 |
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- Precision: 0.9822 |
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- Recall: 0.9828 |
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- False Positive Rate: 0.0178 |
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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: 2e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | False Positive Rate | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:-------------------:| |
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| 0.355 | 1.0 | 3025 | 0.3506 | 0.9625 | 0.9753 | 0.9491 | 0.0240 | |
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| 0.3533 | 2.0 | 6050 | 0.3486 | 0.9641 | 0.9837 | 0.9438 | 0.0156 | |
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| 0.393 | 3.0 | 9075 | 0.3523 | 0.9609 | 0.9863 | 0.9348 | 0.0130 | |
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| 0.3311 | 4.0 | 12100 | 0.3307 | 0.9825 | 0.9822 | 0.9828 | 0.0178 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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