readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - amazon_polarity
  metrics:
  - accuracy
  model-index:
  - name: amazonPolarity_ELECTRA_5E
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: amazon_polarity
        type: amazon_polarity
        config: amazon_polarity
        split: train
        args: amazon_polarity
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9333333333333333
  ---
  
  <!-- 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. -->
  
  # amazonPolarity_ELECTRA_5E
  
  This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the amazon_polarity dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3512
  - Accuracy: 0.9333
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6705        | 0.03  | 50   | 0.5768          | 0.8867   |
  | 0.4054        | 0.05  | 100  | 0.2968          | 0.8933   |
  | 0.2461        | 0.08  | 150  | 0.2233          | 0.92     |
  | 0.1795        | 0.11  | 200  | 0.2265          | 0.9333   |
  | 0.2293        | 0.13  | 250  | 0.2329          | 0.9267   |
  | 0.1541        | 0.16  | 300  | 0.2240          | 0.94     |
  | 0.2006        | 0.19  | 350  | 0.2779          | 0.92     |
  | 0.1826        | 0.21  | 400  | 0.2765          | 0.9133   |
  | 0.1935        | 0.24  | 450  | 0.2346          | 0.9333   |
  | 0.1887        | 0.27  | 500  | 0.2085          | 0.94     |
  | 0.1688        | 0.29  | 550  | 0.2193          | 0.94     |
  | 0.1884        | 0.32  | 600  | 0.1982          | 0.9467   |
  | 0.189         | 0.35  | 650  | 0.1873          | 0.94     |
  | 0.1564        | 0.37  | 700  | 0.2226          | 0.94     |
  | 0.1733        | 0.4   | 750  | 0.2462          | 0.9333   |
  | 0.1436        | 0.43  | 800  | 0.2328          | 0.94     |
  | 0.1517        | 0.45  | 850  | 0.2128          | 0.9533   |
  | 0.1922        | 0.48  | 900  | 0.1626          | 0.9467   |
  | 0.1401        | 0.51  | 950  | 0.2391          | 0.94     |
  | 0.1606        | 0.53  | 1000 | 0.2001          | 0.94     |
  | 0.1597        | 0.56  | 1050 | 0.1788          | 0.9467   |
  | 0.184         | 0.59  | 1100 | 0.1656          | 0.9467   |
  | 0.1448        | 0.61  | 1150 | 0.1752          | 0.96     |
  | 0.1575        | 0.64  | 1200 | 0.1878          | 0.9533   |
  | 0.1836        | 0.67  | 1250 | 0.1416          | 0.9533   |
  | 0.1378        | 0.69  | 1300 | 0.1866          | 0.9467   |
  | 0.1901        | 0.72  | 1350 | 0.1654          | 0.9533   |
  | 0.1697        | 0.75  | 1400 | 0.1720          | 0.9533   |
  | 0.1624        | 0.77  | 1450 | 0.1700          | 0.9467   |
  | 0.1487        | 0.8   | 1500 | 0.1786          | 0.94     |
  | 0.1367        | 0.83  | 1550 | 0.1974          | 0.9267   |
  | 0.1535        | 0.85  | 1600 | 0.1823          | 0.9267   |
  | 0.1366        | 0.88  | 1650 | 0.1515          | 0.94     |
  | 0.1505        | 0.91  | 1700 | 0.1527          | 0.94     |
  | 0.1554        | 0.93  | 1750 | 0.1855          | 0.9467   |
  | 0.1478        | 0.96  | 1800 | 0.1885          | 0.9333   |
  | 0.1603        | 0.99  | 1850 | 0.1990          | 0.9467   |
  | 0.1637        | 1.01  | 1900 | 0.1901          | 0.9467   |
  | 0.1074        | 1.04  | 1950 | 0.1886          | 0.9533   |
  | 0.0874        | 1.07  | 2000 | 0.2399          | 0.94     |
  | 0.1245        | 1.09  | 2050 | 0.2107          | 0.9467   |
  | 0.1175        | 1.12  | 2100 | 0.2226          | 0.94     |
  | 0.1279        | 1.15  | 2150 | 0.2267          | 0.94     |
  | 0.0947        | 1.17  | 2200 | 0.2342          | 0.94     |
  | 0.0837        | 1.2   | 2250 | 0.2519          | 0.9467   |
  | 0.1091        | 1.23  | 2300 | 0.2531          | 0.94     |
  | 0.0867        | 1.25  | 2350 | 0.2519          | 0.94     |
  | 0.0845        | 1.28  | 2400 | 0.2431          | 0.9467   |
  | 0.0836        | 1.31  | 2450 | 0.1936          | 0.9533   |
  | 0.1633        | 1.33  | 2500 | 0.1875          | 0.9333   |
  | 0.1029        | 1.36  | 2550 | 0.2345          | 0.94     |
  | 0.0755        | 1.39  | 2600 | 0.3028          | 0.94     |
  | 0.1539        | 1.41  | 2650 | 0.2497          | 0.94     |
  | 0.1055        | 1.44  | 2700 | 0.2002          | 0.9467   |
  | 0.1234        | 1.47  | 2750 | 0.1763          | 0.9533   |
  | 0.1312        | 1.49  | 2800 | 0.1998     