readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: phishing-bert-base-uncased-finetuned-dsV0
    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. -->
  
  # phishing-bert-base-uncased-finetuned-dsV0
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0194
  - Accuracy: 0.9966
  - F1: 0.9632
  - Precision: 0.9878
  - Recall: 0.9397
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.0361        | 1.0   | 5185  | 0.0197          | 0.9950   | 0.9449 | 0.9911    | 0.9028 |
  | 0.0106        | 2.0   | 10370 | 0.0202          | 0.9959   | 0.9553 | 0.9940    | 0.9195 |
  | 0.0039        | 3.0   | 15555 | 0.0194          | 0.9966   | 0.9632 | 0.9878    | 0.9397 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.9.0+cu111
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  