readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: TUF_ELECTRA_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_ELECTRA_5E
  
  This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1195
  - Accuracy: 0.94
  
  ## 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: 1e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6021        | 0.1   | 50   | 0.5770          | 0.7533   |
  | 0.5301        | 0.2   | 100  | 0.5460          | 0.7533   |
  | 0.4958        | 0.3   | 150  | 0.4943          | 0.7533   |
  | 0.4347        | 0.4   | 200  | 0.4112          | 0.8467   |
  | 0.3565        | 0.5   | 250  | 0.3601          | 0.88     |
  | 0.3515        | 0.59  | 300  | 0.3465          | 0.9      |
  | 0.301         | 0.69  | 350  | 0.3214          | 0.9067   |
  | 0.2963        | 0.79  | 400  | 0.2996          | 0.9      |
  | 0.2848        | 0.89  | 450  | 0.2511          | 0.9267   |
  | 0.2548        | 0.99  | 500  | 0.2493          | 0.8933   |
  | 0.2527        | 1.09  | 550  | 0.2381          | 0.9333   |
  | 0.2484        | 1.19  | 600  | 0.2099          | 0.9333   |
  | 0.2267        | 1.29  | 650  | 0.1834          | 0.9333   |
  | 0.2147        | 1.39  | 700  | 0.1919          | 0.94     |
  | 0.1961        | 1.49  | 750  | 0.1751          | 0.9333   |
  | 0.1868        | 1.58  | 800  | 0.1772          | 0.9267   |
  | 0.2393        | 1.68  | 850  | 0.1726          | 0.92     |
  | 0.1747        | 1.78  | 900  | 0.1509          | 0.9467   |
  | 0.2236        | 1.88  | 950  | 0.1532          | 0.94     |
  | 0.174         | 1.98  | 1000 | 0.1752          | 0.9267   |
  | 0.1983        | 2.08  | 1050 | 0.1563          | 0.94     |
  | 0.2015        | 2.18  | 1100 | 0.1494          | 0.9467   |
  | 0.1563        | 2.28  | 1150 | 0.1876          | 0.9333   |
  | 0.168         | 2.38  | 1200 | 0.1802          | 0.9333   |
  | 0.2074        | 2.48  | 1250 | 0.1669          | 0.94     |
  | 0.1726        | 2.57  | 1300 | 0.1348          | 0.9533   |
  | 0.1373        | 2.67  | 1350 | 0.1549          | 0.9533   |
  | 0.1694        | 2.77  | 1400 | 0.1339          | 0.96     |
  | 0.1782        | 2.87  | 1450 | 0.1417          | 0.9533   |
  | 0.1771        | 2.97  | 1500 | 0.1228          | 0.96     |
  | 0.1886        | 3.07  | 1550 | 0.1415          | 0.9533   |
  | 0.1507        | 3.17  | 1600 | 0.1350          | 0.9467   |
  | 0.1435        | 3.27  | 1650 | 0.1294          | 0.9467   |
  | 0.1548        | 3.37  | 1700 | 0.1316          | 0.96     |
  | 0.1475        | 3.47  | 1750 | 0.1314          | 0.9333   |
  | 0.1764        | 3.56  | 1800 | 0.1195          | 0.94     |
  | 0.1668        | 3.66  | 1850 | 0.1199          | 0.94     |
  | 0.1336        | 3.76  | 1900 | 0.1210          | 0.9467   |
  | 0.1452        | 3.86  | 1950 | 0.1259          | 0.9467   |
  | 0.206         | 3.96  | 2000 | 0.1247          | 0.96     |
  | 0.1704        | 4.06  | 2050 | 0.1253          | 0.9533   |
  | 0.1489        | 4.16  | 2100 | 0.1194          | 0.94     |
  | 0.1766        | 4.26  | 2150 | 0.1278          | 0.96     |
  | 0.1387        | 4.36  | 2200 | 0.1179          | 0.94     |
  | 0.1269        | 4.46  | 2250 | 0.1270          | 0.96     |
  | 0.154         | 4.55  | 2300 | 0.1208          | 0.94     |
  | 0.1481        | 4.65  | 2350 | 0.1210          | 0.94     |
  | 0.1676        | 4.75  | 2400 | 0.1196          | 0.94     |
  | 0.1202        | 4.85  | 2450 | 0.1194          | 0.94     |
  | 0.1323        | 4.95  | 2500 | 0.1195          | 0.94     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  