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library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-phishing-classifier
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-phishing-classifier
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.
It achieves the following results on the evaluation set:
- Loss: 0.2994
- Accuracy: 0.871
- Auc: 0.951
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.4954 | 1.0 | 263 | 0.4188 | 0.791 | 0.913 |
| 0.3914 | 2.0 | 526 | 0.3616 | 0.818 | 0.931 |
| 0.3813 | 3.0 | 789 | 0.3164 | 0.86 | 0.938 |
| 0.3589 | 4.0 | 1052 | 0.4471 | 0.811 | 0.942 |
| 0.3513 | 5.0 | 1315 | 0.3300 | 0.862 | 0.946 |
| 0.3547 | 6.0 | 1578 | 0.3082 | 0.867 | 0.948 |
| 0.3224 | 7.0 | 1841 | 0.2914 | 0.864 | 0.949 |
| 0.3301 | 8.0 | 2104 | 0.2986 | 0.876 | 0.949 |
| 0.3165 | 9.0 | 2367 | 0.2901 | 0.862 | 0.95 |
| 0.3061 | 10.0 | 2630 | 0.2994 | 0.871 | 0.951 |
### Framework versions
- Transformers 5.9.0
- Pytorch 2.11.0
- Datasets 4.8.5
- Tokenizers 0.22.2
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