readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: TUF_BERT_5E
    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. -->
  
  # TUF_BERT_5E
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3251
  - Accuracy: 0.9467
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.4078        | 0.1   | 50   | 0.2430          | 0.92     |
  | 0.2488        | 0.2   | 100  | 0.1465          | 0.94     |
  | 0.1966        | 0.3   | 150  | 0.1284          | 0.96     |
  | 0.2096        | 0.4   | 200  | 0.2879          | 0.9067   |
  | 0.2015        | 0.5   | 250  | 0.1629          | 0.9467   |
  | 0.1692        | 0.59  | 300  | 0.2165          | 0.9133   |
  | 0.1794        | 0.69  | 350  | 0.1535          | 0.9533   |
  | 0.1975        | 0.79  | 400  | 0.1429          | 0.9333   |
  | 0.1394        | 0.89  | 450  | 0.2384          | 0.92     |
  | 0.191         | 0.99  | 500  | 0.2198          | 0.94     |
  | 0.0907        | 1.09  | 550  | 0.1270          | 0.9467   |
  | 0.073         | 1.19  | 600  | 0.2016          | 0.94     |
  | 0.1594        | 1.29  | 650  | 0.2078          | 0.9267   |
  | 0.087         | 1.39  | 700  | 0.3312          | 0.9333   |
  | 0.0961        | 1.49  | 750  | 0.3704          | 0.92     |
  | 0.1225        | 1.58  | 800  | 0.1686          | 0.9467   |
  | 0.0969        | 1.68  | 850  | 0.1525          | 0.9333   |
  | 0.0942        | 1.78  | 900  | 0.1924          | 0.94     |
  | 0.0681        | 1.88  | 950  | 0.1825          | 0.9467   |
  | 0.1295        | 1.98  | 1000 | 0.1360          | 0.9333   |
  | 0.0626        | 2.08  | 1050 | 0.2014          | 0.94     |
  | 0.0372        | 2.18  | 1100 | 0.2030          | 0.9467   |
  | 0.0077        | 2.28  | 1150 | 0.2615          | 0.9467   |
  | 0.0393        | 2.38  | 1200 | 0.4256          | 0.9267   |
  | 0.0492        | 2.48  | 1250 | 0.3057          | 0.94     |
  | 0.0184        | 2.57  | 1300 | 0.1308          | 0.9733   |
  | 0.0209        | 2.67  | 1350 | 0.2848          | 0.9467   |
  | 0.0328        | 2.77  | 1400 | 0.1862          | 0.96     |
  | 0.0333        | 2.87  | 1450 | 0.2347          | 0.96     |
  | 0.0527        | 2.97  | 1500 | 0.3855          | 0.9333   |
  | 0.0685        | 3.07  | 1550 | 0.3174          | 0.94     |
  | 0.0217        | 3.17  | 1600 | 0.2320          | 0.9533   |
  | 0.0036        | 3.27  | 1650 | 0.3219          | 0.9333   |
  | 0.0015        | 3.37  | 1700 | 0.1649          | 0.9733   |
  | 0.0177        | 3.47  | 1750 | 0.3785          | 0.94     |
  | 0.0142        | 3.56  | 1800 | 0.1420          | 0.9733   |
  | 0.0319        | 3.66  | 1850 | 0.4057          | 0.9333   |
  | 0.0254        | 3.76  | 1900 | 0.1824          | 0.96     |
  | 0.0092        | 3.86  | 1950 | 0.2400          | 0.9533   |
  | 0.0306        | 3.96  | 2000 | 0.2238          | 0.96     |
  | 0.0118        | 4.06  | 2050 | 0.2623          | 0.9533   |
  | 0.0097        | 4.16  | 2100 | 0.3642          | 0.9467   |
  | 0.0132        | 4.26  | 2150 | 0.3235          | 0.9467   |
  | 0.0155        | 4.36  | 2200 | 0.3535          | 0.9467   |
  | 0.0043        | 4.46  | 2250 | 0.3236          | 0.9467   |
  | 0.0004        | 4.55  | 2300 | 0.2984          | 0.9467   |
  | 0.009         | 4.65  | 2350 | 0.2941          | 0.9467   |
  | 0.0068        | 4.75  | 2400 | 0.2936          | 0.9467   |
  | 0.0102        | 4.85  | 2450 | 0.3138          | 0.9467   |
  | 0.0015        | 4.95  | 2500 | 0.3251          | 0.9467   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  