readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: website_classification
    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. -->
  
  # website_classification
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2292
  - Accuracy: 0.9504
  - F1: 0.9489
  - Precision: 0.9510
  - Recall: 0.9504
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 2.404         | 1.0   | 71   | 1.7840          | 0.8865   | 0.8776 | 0.8785    | 0.8865 |
  | 1.295         | 2.0   | 142  | 0.8539          | 0.8972   | 0.8871 | 0.8803    | 0.8972 |
  | 0.6186        | 3.0   | 213  | 0.4818          | 0.9326   | 0.9263 | 0.9266    | 0.9326 |
  | 0.3103        | 4.0   | 284  | 0.3101          | 0.9397   | 0.9343 | 0.9324    | 0.9397 |
  | 0.1618        | 5.0   | 355  | 0.3001          | 0.9291   | 0.9251 | 0.9278    | 0.9291 |
  | 0.0893        | 6.0   | 426  | 0.2743          | 0.9291   | 0.9251 | 0.9276    | 0.9291 |
  | 0.0547        | 7.0   | 497  | 0.2605          | 0.9255   | 0.9236 | 0.9334    | 0.9255 |
  | 0.028         | 8.0   | 568  | 0.2167          | 0.9397   | 0.9375 | 0.9403    | 0.9397 |
  | 0.0186        | 9.0   | 639  | 0.2096          | 0.9468   | 0.9467 | 0.9499    | 0.9468 |
  | 0.0134        | 10.0  | 710  | 0.2219          | 0.9362   | 0.9354 | 0.9402    | 0.9362 |
  | 0.0107        | 11.0  | 781  | 0.2124          | 0.9468   | 0.9466 | 0.9507    | 0.9468 |
  | 0.0087        | 12.0  | 852  | 0.2119          | 0.9504   | 0.9497 | 0.9534    | 0.9504 |
  | 0.0075        | 13.0  | 923  | 0.2141          | 0.9504   | 0.9497 | 0.9534    | 0.9504 |
  | 0.0066        | 14.0  | 994  | 0.2198          | 0.9433   | 0.9415 | 0.9442    | 0.9433 |
  | 0.0058        | 15.0  | 1065 | 0.2188          | 0.9468   | 0.9454 | 0.9474    | 0.9468 |
  | 0.0052        | 16.0  | 1136 | 0.2181          | 0.9468   | 0.9454 | 0.9474    | 0.9468 |
  | 0.0047        | 17.0  | 1207 | 0.2220          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.0044        | 18.0  | 1278 | 0.2232          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.004         | 19.0  | 1349 | 0.2216          | 0.9539   | 0.9535 | 0.9565    | 0.9539 |
  | 0.0037        | 20.0  | 1420 | 0.2251          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.0036        | 21.0  | 1491 | 0.2275          | 0.9468   | 0.9451 | 0.9470    | 0.9468 |
  | 0.0034        | 22.0  | 1562 | 0.2264          | 0.9539   | 0.9535 | 0.9565    | 0.9539 |
  | 0.0032        | 23.0  | 1633 | 0.2283          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.003         | 24.0  | 1704 | 0.2299          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.0029        | 25.0  | 1775 | 0.2282          | 0.9468   | 0.9451 | 0.9470    | 0.9468 |
  | 0.0029        | 26.0  | 1846 | 0.2288          | 0.9468   | 0.9451 | 0.9470    | 0.9468 |
  | 0.0028        | 27.0  | 1917 | 0.2286          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.0027        | 28.0  | 1988 | 0.2293          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.0026        | 29.0  | 2059 | 0.2291          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  | 0.0026        | 30.0  | 2130 | 0.2292          | 0.9504   | 0.9489 | 0.9510    | 0.9504 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  