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# Baseline_100Kphish_benignFall_5_20_20

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_benign_200K_top_p_0.75 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0216
- Accuracy: 0.9976
- F1: 0.9745
- Precision: 0.9989
- Recall: 0.9512
- Roc Auc Score: 0.9756
- Tpr At Fpr 0.01: 0.9544

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------:|:---------------:|
| 0.0079        | 1.0   | 18750 | 0.0117          | 0.9976   | 0.9749 | 0.9923    | 0.958  | 0.9788        | 0.876           |
| 0.0057        | 2.0   | 37500 | 0.0255          | 0.9955   | 0.9509 | 0.9987    | 0.9074 | 0.9537        | 0.926           |
| 0.0025        | 3.0   | 56250 | 0.0166          | 0.9976   | 0.9748 | 0.9967    | 0.9538 | 0.9768        | 0.948           |
| 0.0016        | 4.0   | 75000 | 0.0187          | 0.9978   | 0.9765 | 0.9956    | 0.958  | 0.9789        | 0.9468          |
| 0.0008        | 5.0   | 93750 | 0.0216          | 0.9976   | 0.9745 | 0.9989    | 0.9512 | 0.9756        | 0.9544          |


### 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": "Baseline_100Kphish_benignFall_5_20_20", "results": []}]}
tensorboard generated_from_trainer license:apache-2.0 region:us
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 

Baseline\_100Kphish\_benignFall\_5\_20\_20
==========================================


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\_benign\_200K\_top\_p\_0.75 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0216
* Accuracy: 0.9976
* F1: 0.9745
* Precision: 0.9989
* Recall: 0.9512
* Roc Auc Score: 0.9756
* Tpr At Fpr 0.01: 0.9544


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