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# OnlyPhishGPT2_Domain_100KP_BFall_fromB_100K_topP_0.75_ratio2.5

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_OnlyPhishGPT2_using_benign_100K_top_p_0.75_domain dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0200
- Accuracy: 0.9976
- F1: 0.9747
- Precision: 0.9881
- Recall: 0.9616
- Roc Auc Score: 0.9805
- Tpr At Fpr 0.01: 0.0

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     | Precision | Recall | Roc Auc Score | Tpr At Fpr 0.01 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------:|:---------------:|
| 0.0156        | 1.0   | 21875  | 0.0161          | 0.9962   | 0.9602 | 0.9710    | 0.9496 | 0.9741        | 0.836           |
| 0.0094        | 2.0   | 43750  | 0.0124          | 0.9973   | 0.9709 | 0.9884    | 0.954  | 0.9767        | 0.9             |
| 0.0042        | 3.0   | 65625  | 0.0174          | 0.9970   | 0.9678 | 0.9735    | 0.9622 | 0.9804        | 0.8922          |
| 0.0021        | 4.0   | 87500  | 0.0203          | 0.9974   | 0.9724 | 0.9836    | 0.9614 | 0.9803        | 0.0             |
| 0.0           | 5.0   | 109375 | 0.0200          | 0.9976   | 0.9747 | 0.9881    | 0.9616 | 0.9805        | 0.0             |


### Framework versions

- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "OnlyPhishGPT2_Domain_100KP_BFall_fromB_100K_topP_0.75_ratio2.5", "results": []}]}
tensorboard generated_from_trainer license:apache-2.0 region:us
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 

OnlyPhishGPT2\_Domain\_100KP\_BFall\_fromB\_100K\_topP\_0.75\_ratio2.5
======================================================================


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\_OnlyPhishGPT2\_using\_benign\_100K\_top\_p\_0.75\_domain dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0200
* Accuracy: 0.9976
* F1: 0.9747
* Precision: 0.9881
* Recall: 0.9616
* Roc Auc Score: 0.9805
* Tpr At Fpr 0.01: 0.0


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
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.1
* Pytorch 1.9.0+cu111
* Datasets 2.10.1
* Tokenizers 0.13.2



### 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
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.1
* Pytorch 1.9.0+cu111
* Datasets 2.10.1
* Tokenizers 0.13.2
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
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.1
* Pytorch 1.9.0+cu111
* Datasets 2.10.1
* Tokenizers 0.13.2