readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: phishing-distilbert-base-uncased-finetuned-dsV1.1_128maxlength
    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-distilbert-base-uncased-finetuned-dsV1.1_128maxlength
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0203
  - Accuracy: 0.9961
  - F1: 0.9581
  - Precision: 0.9866
  - Recall: 0.9311
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.0345        | 1.0   | 5185  | 0.0256          | 0.9940   | 0.9332 | 0.9926    | 0.8805 |
  | 0.0109        | 2.0   | 10370 | 0.0195          | 0.9955   | 0.9511 | 0.9939    | 0.9119 |
  | 0.0045        | 3.0   | 15555 | 0.0203          | 0.9961   | 0.9581 | 0.9866    | 0.9311 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.9.0+cu111
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  