readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  model-index:
  - name: IMDB_DistilBERT_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: 0.9333333333333333
  ---
  
  <!-- 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. -->
  
  # IMDB_DistilBERT_5E
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2309
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6706        | 0.03  | 50   | 0.5746          | 0.8533   |
  | 0.4323        | 0.06  | 100  | 0.2900          | 0.9      |
  | 0.314         | 0.1   | 150  | 0.2334          | 0.9067   |
  | 0.3062        | 0.13  | 200  | 0.1884          | 0.94     |
  | 0.2834        | 0.16  | 250  | 0.1880          | 0.9267   |
  | 0.2751        | 0.19  | 300  | 0.1944          | 0.94     |
  | 0.2258        | 0.22  | 350  | 0.2003          | 0.9267   |
  | 0.2631        | 0.26  | 400  | 0.1507          | 0.9467   |
  | 0.2661        | 0.29  | 450  | 0.1536          | 0.9467   |
  | 0.2481        | 0.32  | 500  | 0.1533          | 0.94     |
  | 0.2746        | 0.35  | 550  | 0.1402          | 0.9533   |
  | 0.2539        | 0.38  | 600  | 0.1331          | 0.94     |
  | 0.2673        | 0.42  | 650  | 0.1404          | 0.9467   |
  | 0.2438        | 0.45  | 700  | 0.1213          | 0.96     |
  | 0.2355        | 0.48  | 750  | 0.1181          | 0.9533   |
  | 0.2059        | 0.51  | 800  | 0.1417          | 0.9333   |
  | 0.2585        | 0.54  | 850  | 0.1257          | 0.9533   |
  | 0.2331        | 0.58  | 900  | 0.1307          | 0.94     |
  | 0.2602        | 0.61  | 950  | 0.1172          | 0.9467   |
  | 0.24          | 0.64  | 1000 | 0.1141          | 0.9533   |
  | 0.2169        | 0.67  | 1050 | 0.1198          | 0.94     |
  | 0.2796        | 0.7   | 1100 | 0.1171          | 0.9533   |
  | 0.2559        | 0.74  | 1150 | 0.1199          | 0.96     |
  | 0.2377        | 0.77  | 1200 | 0.1359          | 0.9333   |
  | 0.2268        | 0.8   | 1250 | 0.1235          | 0.9533   |
  | 0.2422        | 0.83  | 1300 | 0.1439          | 0.9333   |
  | 0.2101        | 0.86  | 1350 | 0.1333          | 0.9333   |
  | 0.1875        | 0.9   | 1400 | 0.1206          | 0.9467   |
  | 0.2279        | 0.93  | 1450 | 0.1136          | 0.96     |
  | 0.2214        | 0.96  | 1500 | 0.1188          | 0.9467   |
  | 0.2416        | 0.99  | 1550 | 0.1029          | 0.9467   |
  | 0.219         | 1.02  | 1600 | 0.1113          | 0.94     |
  | 0.1806        | 1.06  | 1650 | 0.1095          | 0.9533   |
  | 0.1343        | 1.09  | 1700 | 0.1630          | 0.94     |
  | 0.1699        | 1.12  | 1750 | 0.1221          | 0.96     |
  | 0.1837        | 1.15  | 1800 | 0.1213          | 0.9467   |
  | 0.1763        | 1.18  | 1850 | 0.1286          | 0.9533   |
  | 0.1856        | 1.22  | 1900 | 0.1531          | 0.9267   |
  | 0.1647        | 1.25  | 1950 | 0.1380          | 0.9533   |
  | 0.2204        | 1.28  | 2000 | 0.1268          | 0.9333   |
  | 0.1774        | 1.31  | 2050 | 0.1689          | 0.9267   |
  | 0.2052        | 1.34  | 2100 | 0.1317          | 0.94     |
  | 0.1728        | 1.38  | 2150 | 0.1286          | 0.9533   |
  | 0.1816        | 1.41  | 2200 | 0.1280          | 0.9333   |
  | 0.1574        | 1.44  | 2250 | 0.1363          | 0.94     |
  | 0.1907        | 1.47  | 2300 | 0.1229          | 0.9533   |
  | 0.2032        | 1.5   | 2350 | 0.1036          | 0.96     |
  | 0.1636        | 1.54  | 2400 | 0.1061          | 0.9533   |
  | 0.1795        | 1.57  | 2450 | 0.1414          | 0.9333   |
  | 0.1497        | 1.6   | 2500 | 0.1401          | 0.94     |
  | 0.2026        | 1.63  | 2550 | 0.1462          | 0.9333   |
  | 0.1797        | 1.66  | 2600 | 0.1355          | 0.9467   |
  | 0.1612        | 1.7   | 2650 | 0.1283          | 0.9533   |
  | 0.1922        | 1.73  | 2700 | 0.1235          | 0.9467   |
  | 0.1321        | 1.76  | 2750 | 0.1336          | 0.9467   |
  | 0.1908        | 1.79  | 2800 | 0.1518          | 0.94     |
  | 0.1684        | 1.82  | 2850 | 0.1394          | 0.9533   |
  | 0.1746