readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - yelp_review_full
  metrics:
  - accuracy
  model-index:
  - name: YELP_ELECTRA_5E
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: yelp_review_full
        type: yelp_review_full
        config: yelp_review_full
        split: train
        args: yelp_review_full
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.96
  ---
  
  <!-- 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. -->
  
  # YELP_ELECTRA_5E
  
  This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the yelp_review_full dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1658
  - Accuracy: 0.96
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6872        | 0.03  | 50   | 0.6751          | 0.5867   |
  | 0.6407        | 0.06  | 100  | 0.5811          | 0.86     |
  | 0.5551        | 0.1   | 150  | 0.4980          | 0.8667   |
  | 0.4784        | 0.13  | 200  | 0.3889          | 0.9333   |
  | 0.412         | 0.16  | 250  | 0.3349          | 0.9333   |
  | 0.3826        | 0.19  | 300  | 0.3138          | 0.9133   |
  | 0.3629        | 0.22  | 350  | 0.2568          | 0.96     |
  | 0.335         | 0.26  | 400  | 0.2352          | 0.9333   |
  | 0.2966        | 0.29  | 450  | 0.1907          | 0.9667   |
  | 0.2776        | 0.32  | 500  | 0.1898          | 0.96     |
  | 0.2428        | 0.35  | 550  | 0.1771          | 0.9533   |
  | 0.2577        | 0.38  | 600  | 0.1610          | 0.96     |
  | 0.2252        | 0.42  | 650  | 0.1503          | 0.96     |
  | 0.2273        | 0.45  | 700  | 0.1425          | 0.9667   |
  | 0.2155        | 0.48  | 750  | 0.1417          | 0.96     |
  | 0.2681        | 0.51  | 800  | 0.1682          | 0.94     |
  | 0.195         | 0.54  | 850  | 0.1527          | 0.96     |
  | 0.2133        | 0.58  | 900  | 0.1480          | 0.9533   |
  | 0.1996        | 0.61  | 950  | 0.1516          | 0.9533   |
  | 0.2123        | 0.64  | 1000 | 0.1645          | 0.94     |
  | 0.2263        | 0.67  | 1050 | 0.1449          | 0.96     |
  | 0.1941        | 0.7   | 1100 | 0.1445          | 0.96     |
  | 0.2273        | 0.74  | 1150 | 0.1389          | 0.96     |
  | 0.2156        | 0.77  | 1200 | 0.1541          | 0.9533   |
  | 0.193         | 0.8   | 1250 | 0.1512          | 0.9533   |
  | 0.1851        | 0.83  | 1300 | 0.1949          | 0.92     |
  | 0.2041        | 0.86  | 1350 | 0.1531          | 0.96     |
  | 0.1924        | 0.9   | 1400 | 0.1640          | 0.9533   |
  | 0.2453        | 0.93  | 1450 | 0.1639          | 0.9467   |
  | 0.1774        | 0.96  | 1500 | 0.1729          | 0.9467   |
  | 0.1999        | 0.99  | 1550 | 0.1618          | 0.94     |
  | 0.1998        | 1.02  | 1600 | 0.1628          | 0.9467   |
  | 0.1607        | 1.06  | 1650 | 0.1608          | 0.94     |
  | 0.1878        | 1.09  | 1700 | 0.1659          | 0.9467   |
  | 0.1702        | 1.12  | 1750 | 0.1694          | 0.9467   |
  | 0.1711        | 1.15  | 1800 | 0.1666          | 0.9467   |
  | 0.1517        | 1.18  | 1850 | 0.1560          | 0.9533   |
  | 0.1521        | 1.22  | 1900 | 0.1662          | 0.9467   |
  | 0.2297        | 1.25  | 1950 | 0.2137          | 0.94     |
  | 0.2046        | 1.28  | 2000 | 0.1793          | 0.94     |
  | 0.1869        | 1.31  | 2050 | 0.1673          | 0.9467   |
  | 0.1684        | 1.34  | 2100 | 0.1730          | 0.9467   |
  | 0.1359        | 1.38  | 2150 | 0.1817          | 0.94     |
  | 0.1595        | 1.41  | 2200 | 0.1709          | 0.9467   |
  | 0.1458        | 1.44  | 2250 | 0.1660          | 0.94     |
  | 0.1518        | 1.47  | 2300 | 0.1735          | 0.9467   |
  | 0.1239        | 1.5   | 2350 | 0.1514          | 0.9533   |
  | 0.2183        | 1.54  | 2400 | 0.1644          | 0.9467   |
  | 0.1678        | 1.57  | 2450 | 0.1578          | 0.9467   |
  | 0.1516        | 1.6   | 2500 | 0.1562          | 0.9467   |
  | 0.2575        | 1.63  | 2550 | 0.1516          | 0.9467   |
  | 0.1576        | 1.66  | 2600 | 0.1684          | 0.9533   |
  | 0.1134        | 1.7   | 2650 | 0.1691          | 0.96     |
  | 0.2075        | 1.73  | 2700 | 0.1586          | 0.96     |
  | 0.1425        | 1.76  | 2750 | 0.1516          | 0.96     |
  | 0.1426        | 1.79  | 2800 | 0.1499          | 0.96     |
  | 0.1295  