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# MixGPT2_Suffix_100KP_BFall_fromP_90K_topP_0.75_ratio2.63

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the Train benign: Fall,Test Benign: Fall, Train phish: Fall, Test phish: Fall, generated url dataset: generated_phish_MixGPT2_using_benigh_95K_top_p_0.75suffix dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0234
- Accuracy: 0.9975
- F1: 0.9731
- Precision: 0.9985
- Recall: 0.949
- Roc Auc Score: 0.9745
- Tpr At Fpr 0.01: 0.9546

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     | Precision | Recall | Roc Auc Score | Tpr At Fpr 0.01 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------:|:---------------:|
| 0.0054        | 1.0   | 21554  | 0.0145          | 0.997    | 0.9676 | 0.9972    | 0.9396 | 0.9697        | 0.9348          |
| 0.0041        | 2.0   | 43108  | 0.0160          | 0.9974   | 0.9718 | 0.9975    | 0.9474 | 0.9736        | 0.9366          |
| 0.0019        | 3.0   | 64662  | 0.0142          | 0.9977   | 0.9755 | 0.9969    | 0.955  | 0.9774        | 0.9438          |
| 0.0009        | 4.0   | 86216  | 0.0135          | 0.9982   | 0.9803 | 0.9946    | 0.9664 | 0.9831        | 0.9522          |
| 0.0001        | 5.0   | 107770 | 0.0234          | 0.9975   | 0.9731 | 0.9985    | 0.949  | 0.9745        | 0.9546          |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "MixGPT2_Suffix_100KP_BFall_fromP_90K_topP_0.75_ratio2.63", "results": []}]}
tensorboard generated_from_trainer license:apache-2.0 region:us
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 

MixGPT2\_Suffix\_100KP\_BFall\_fromP\_90K\_topP\_0.75\_ratio2.63
================================================================


This model is a fine-tuned version of bert-base-uncased on the Train benign: Fall,Test Benign: Fall, Train phish: Fall, Test phish: Fall, generated url dataset: generated\_phish\_MixGPT2\_using\_benigh\_95K\_top\_p\_0.75suffix dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0234
* Accuracy: 0.9975
* F1: 0.9731
* Precision: 0.9985
* Recall: 0.949
* Roc Auc Score: 0.9745
* Tpr At Fpr 0.01: 0.9546


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: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5.0


### Training results



### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3