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bert-finetuned-phishing

Text Classification
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PyTorch
English
bert
Generated from Trainer
phishing
BERT
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End of training

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  1. README.md +11 -10
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1953
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- - Accuracy: 0.9717
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- - Precision: 0.9658
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- - Recall: 0.9670
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- - False Positive Rate: 0.0249
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  ## Model description
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@@ -48,16 +48,17 @@ The following hyperparameters were used during training:
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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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- | 0.1487 | 1.0 | 3866 | 0.1454 | 0.9596 | 0.9709 | 0.9320 | 0.0203 |
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- | 0.0805 | 2.0 | 7732 | 0.1389 | 0.9691 | 0.9663 | 0.9601 | 0.0243 |
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- | 0.0389 | 3.0 | 11598 | 0.1779 | 0.9683 | 0.9778 | 0.9461 | 0.0156 |
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- | 0.0091 | 4.0 | 15464 | 0.1953 | 0.9717 | 0.9658 | 0.9670 | 0.0249 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2244
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+ - Accuracy: 0.9701
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+ - Precision: 0.9648
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+ - Recall: 0.9642
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+ - False Positive Rate: 0.0256
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  ## Model description
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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: 5
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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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+ | 0.1491 | 1.0 | 3866 | 0.1317 | 0.9614 | 0.9623 | 0.9453 | 0.0269 |
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+ | 0.095 | 2.0 | 7732 | 0.1663 | 0.9628 | 0.9799 | 0.9306 | 0.0138 |
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+ | 0.0429 | 3.0 | 11598 | 0.1882 | 0.9659 | 0.9751 | 0.9430 | 0.0175 |
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+ | 0.0225 | 4.0 | 15464 | 0.1959 | 0.9698 | 0.9638 | 0.9645 | 0.0264 |
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+ | 0.0054 | 5.0 | 19330 | 0.2244 | 0.9701 | 0.9648 | 0.9642 | 0.0256 |
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  ### Framework versions
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