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# Onlyphish_100KP_BFall_fromB_40KGen_topP_0.75_noaddedB

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_40K_top_p_0.75 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0177
- Accuracy: 0.9976
- F1: 0.9746
- Precision: 0.9994
- Recall: 0.951
- Roc Auc Score: 0.9755
- Tpr At Fpr 0.01: 0.965

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------:|:---------------:|
| 0.0034        | 1.0   | 66875  | 0.0124          | 0.9970   | 0.9680 | 0.9926    | 0.9446 | 0.9721        | 0.9258          |
| 0.0015        | 2.0   | 133750 | 0.0227          | 0.9969   | 0.9667 | 0.9974    | 0.9378 | 0.9688        | 0.9346          |
| 0.0011        | 3.0   | 200625 | 0.0224          | 0.9969   | 0.9669 | 0.9991    | 0.9366 | 0.9683        | 0.9476          |
| 0.0005        | 4.0   | 267500 | 0.0200          | 0.9975   | 0.9731 | 0.9992    | 0.9484 | 0.9742        | 0.9618          |
| 0.0006        | 5.0   | 334375 | 0.0177          | 0.9976   | 0.9746 | 0.9994    | 0.951  | 0.9755        | 0.965           |


### 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": "Onlyphish_100KP_BFall_fromB_40KGen_topP_0.75_noaddedB", "results": []}]}
tensorboard generated_from_trainer license:apache-2.0 region:us
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 

Onlyphish\_100KP\_BFall\_fromB\_40KGen\_topP\_0.75\_noaddedB
============================================================


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\_40K\_top\_p\_0.75 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0177
* Accuracy: 0.9976
* F1: 0.9746
* Precision: 0.9994
* Recall: 0.951
* Roc Auc Score: 0.9755
* Tpr At Fpr 0.01: 0.965


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