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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: google-bert/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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model-index: |
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- name: bert-phishing-classifier_teacher |
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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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# bert-phishing-classifier_teacher |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2855 |
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- Accuracy: 0.873 |
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- Auc: 0.952 |
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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: 0.0002 |
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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 OptimizerNames.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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:| |
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| 0.5029 | 1.0 | 263 | 0.3806 | 0.813 | 0.913 | |
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| 0.4031 | 2.0 | 526 | 0.3636 | 0.847 | 0.934 | |
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| 0.3878 | 3.0 | 789 | 0.3134 | 0.844 | 0.94 | |
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| 0.35 | 4.0 | 1052 | 0.3951 | 0.842 | 0.945 | |
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| 0.3331 | 5.0 | 1315 | 0.3176 | 0.867 | 0.947 | |
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| 0.3523 | 6.0 | 1578 | 0.2938 | 0.869 | 0.95 | |
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| 0.3171 | 7.0 | 1841 | 0.2859 | 0.869 | 0.95 | |
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| 0.3206 | 8.0 | 2104 | 0.2811 | 0.873 | 0.952 | |
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| 0.295 | 9.0 | 2367 | 0.2800 | 0.873 | 0.952 | |
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| 0.3035 | 10.0 | 2630 | 0.2855 | 0.873 | 0.952 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.21.0 |
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