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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_teacher
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_teacher
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: 0.2897
- Accuracy: 0.864
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.5042 | 1.0 | 263 | 0.3865 | 0.813 | 0.912 |
| 0.4105 | 2.0 | 526 | 0.3380 | 0.847 | 0.931 |
| 0.3583 | 3.0 | 789 | 0.3148 | 0.856 | 0.939 |
| 0.3553 | 4.0 | 1052 | 0.3454 | 0.851 | 0.945 |
| 0.3511 | 5.0 | 1315 | 0.3450 | 0.86 | 0.948 |
| 0.3477 | 6.0 | 1578 | 0.2906 | 0.871 | 0.95 |
| 0.3346 | 7.0 | 1841 | 0.2879 | 0.876 | 0.95 |
| 0.3096 | 8.0 | 2104 | 0.2892 | 0.869 | 0.95 |
| 0.3153 | 9.0 | 2367 | 0.2841 | 0.88 | 0.951 |
| 0.3140 | 10.0 | 2630 | 0.2897 | 0.864 | 0.951 |
### Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2