readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  model-index:
  - name: IMDB_ELECTRA_5E
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: imdb
        type: imdb
        config: plain_text
        split: train
        args: plain_text
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9533333333333334
  ---
  
  <!-- 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. -->
  
  # IMDB_ELECTRA_5E
  
  This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the imdb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2158
  - Accuracy: 0.9533
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6784        | 0.03  | 50   | 0.6027          | 0.84     |
  | 0.4378        | 0.06  | 100  | 0.2217          | 0.9533   |
  | 0.3063        | 0.1   | 150  | 0.1879          | 0.94     |
  | 0.2183        | 0.13  | 200  | 0.1868          | 0.9333   |
  | 0.2058        | 0.16  | 250  | 0.1548          | 0.9467   |
  | 0.2287        | 0.19  | 300  | 0.1572          | 0.9533   |
  | 0.1677        | 0.22  | 350  | 0.1472          | 0.9533   |
  | 0.1997        | 0.26  | 400  | 0.1400          | 0.9533   |
  | 0.1966        | 0.29  | 450  | 0.1592          | 0.9333   |
  | 0.184         | 0.32  | 500  | 0.1529          | 0.96     |
  | 0.2084        | 0.35  | 550  | 0.2136          | 0.9067   |
  | 0.2126        | 0.38  | 600  | 0.1508          | 0.9533   |
  | 0.1695        | 0.42  | 650  | 0.1442          | 0.9667   |
  | 0.2506        | 0.45  | 700  | 0.1811          | 0.9467   |
  | 0.1755        | 0.48  | 750  | 0.1336          | 0.96     |
  | 0.1874        | 0.51  | 800  | 0.1403          | 0.9533   |
  | 0.1535        | 0.54  | 850  | 0.1239          | 0.96     |
  | 0.1458        | 0.58  | 900  | 0.1198          | 0.9667   |
  | 0.1649        | 0.61  | 950  | 0.1538          | 0.9533   |
  | 0.2014        | 0.64  | 1000 | 0.1196          | 0.9667   |
  | 0.1651        | 0.67  | 1050 | 0.1200          | 0.96     |
  | 0.1595        | 0.7   | 1100 | 0.1155          | 0.96     |
  | 0.1787        | 0.74  | 1150 | 0.1175          | 0.96     |
  | 0.1666        | 0.77  | 1200 | 0.1264          | 0.9533   |
  | 0.1412        | 0.8   | 1250 | 0.1655          | 0.9533   |
  | 0.1949        | 0.83  | 1300 | 0.1363          | 0.9467   |
  | 0.1485        | 0.86  | 1350 | 0.1434          | 0.9667   |
  | 0.1801        | 0.9   | 1400 | 0.1379          | 0.9667   |
  | 0.178         | 0.93  | 1450 | 0.1498          | 0.96     |
  | 0.1767        | 0.96  | 1500 | 0.1507          | 0.9533   |
  | 0.1452        | 0.99  | 1550 | 0.1340          | 0.94     |
  | 0.1465        | 1.02  | 1600 | 0.1416          | 0.96     |
  | 0.1115        | 1.06  | 1650 | 0.1435          | 0.96     |
  | 0.1212        | 1.09  | 1700 | 0.1379          | 0.96     |
  | 0.1534        | 1.12  | 1750 | 0.1198          | 0.96     |
  | 0.1164        | 1.15  | 1800 | 0.1011          | 0.96     |
  | 0.1383        | 1.18  | 1850 | 0.1043          | 0.96     |
  | 0.1415        | 1.22  | 1900 | 0.0914          | 0.9533   |
  | 0.136         | 1.25  | 1950 | 0.1341          | 0.9533   |
  | 0.1301        | 1.28  | 2000 | 0.1303          | 0.9533   |
  | 0.1486        | 1.31  | 2050 | 0.1027          | 0.9733   |
  | 0.0844        | 1.34  | 2100 | 0.1410          | 0.9667   |
  | 0.1388        | 1.38  | 2150 | 0.1265          | 0.9667   |
  | 0.12          | 1.41  | 2200 | 0.1139          | 0.9667   |
  | 0.1329        | 1.44  | 2250 | 0.1259          | 0.9667   |
  | 0.0982        | 1.47  | 2300 | 0.1349          | 0.9667   |
  | 0.1271        | 1.5   | 2350 | 0.1176          | 0.9667   |
  | 0.1286        | 1.54  | 2400 | 0.1349          | 0.9533   |
  | 0.1079        | 1.57  | 2450 | 0.1335          | 0.96     |
  | 0.1236        | 1.6   | 2500 | 0.1393          | 0.96     |
  | 0.1285        | 1.63  | 2550 | 0.1635          | 0.96     |
  | 0.0932        | 1.66  | 2600 | 0.1571          | 0.9533   |
  | 0.1222        | 1.7   | 2650 | 0.1610          | 0.9533   |
  | 0.1421        | 1.73  | 2700 | 0.1296          | 0.9533   |
  | 0.1581        | 1.76  | 2750 | 0.1289          | 0.96     |
  | 0.1245        | 1.79  | 2800 | 0.1180          | 0.9667   |
  | 0.1196        | 1.82  | 2850 | 0.1371          | 0.96 