readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  model-index:
  - name: IMDB_DistilBERT_5EE
    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: 0.94
  ---
  
  <!-- 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_5EE
  
  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: 0.2023
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6748        | 0.03  | 50   | 0.5955          | 0.88     |
  | 0.4404        | 0.06  | 100  | 0.2853          | 0.9      |
  | 0.3065        | 0.1   | 150  | 0.2208          | 0.9      |
  | 0.3083        | 0.13  | 200  | 0.2023          | 0.9333   |
  | 0.2922        | 0.16  | 250  | 0.1530          | 0.94     |
  | 0.2761        | 0.19  | 300  | 0.2035          | 0.9267   |
  | 0.2145        | 0.22  | 350  | 0.2450          | 0.9      |
  | 0.258         | 0.26  | 400  | 0.1680          | 0.9267   |
  | 0.2702        | 0.29  | 450  | 0.1607          | 0.9333   |
  | 0.2587        | 0.32  | 500  | 0.1496          | 0.9467   |
  | 0.2822        | 0.35  | 550  | 0.1405          | 0.9333   |
  | 0.2538        | 0.38  | 600  | 0.1396          | 0.9467   |
  | 0.2707        | 0.42  | 650  | 0.1626          | 0.9333   |
  | 0.2408        | 0.45  | 700  | 0.1623          | 0.9067   |
  | 0.2531        | 0.48  | 750  | 0.1300          | 0.9467   |
  | 0.2014        | 0.51  | 800  | 0.1529          | 0.9333   |
  | 0.2454        | 0.54  | 850  | 0.1365          | 0.94     |
  | 0.2282        | 0.58  | 900  | 0.1447          | 0.9533   |
  | 0.2554        | 0.61  | 950  | 0.1321          | 0.9467   |
  | 0.24          | 0.64  | 1000 | 0.1256          | 0.9467   |
  | 0.2239        | 0.67  | 1050 | 0.1290          | 0.9467   |
  | 0.2865        | 0.7   | 1100 | 0.1288          | 0.9667   |
  | 0.2456        | 0.74  | 1150 | 0.1299          | 0.9533   |
  | 0.2407        | 0.77  | 1200 | 0.1565          | 0.9267   |
  | 0.2256        | 0.8   | 1250 | 0.1262          | 0.96     |
  | 0.238         | 0.83  | 1300 | 0.1599          | 0.9333   |
  | 0.2151        | 0.86  | 1350 | 0.1252          | 0.9333   |
  | 0.187         | 0.9   | 1400 | 0.1132          | 0.9467   |
  | 0.2218        | 0.93  | 1450 | 0.1030          | 0.9533   |
  | 0.2371        | 0.96  | 1500 | 0.1036          | 0.9467   |
  | 0.2264        | 0.99  | 1550 | 0.1041          | 0.9467   |
  | 0.2159        | 1.02  | 1600 | 0.1338          | 0.9267   |
  | 0.1773        | 1.06  | 1650 | 0.1218          | 0.94     |
  | 0.1381        | 1.09  | 1700 | 0.1593          | 0.94     |
  | 0.1582        | 1.12  | 1750 | 0.1445          | 0.9533   |
  | 0.1921        | 1.15  | 1800 | 0.1355          | 0.94     |
  | 0.206         | 1.18  | 1850 | 0.1511          | 0.9467   |
  | 0.1679        | 1.22  | 1900 | 0.1394          | 0.94     |
  | 0.1691        | 1.25  | 1950 | 0.1403          | 0.9333   |
  | 0.2301        | 1.28  | 2000 | 0.1169          | 0.9467   |
  | 0.1764        | 1.31  | 2050 | 0.1507          | 0.9333   |
  | 0.1772        | 1.34  | 2100 | 0.1148          | 0.96     |
  | 0.1749        | 1.38  | 2150 | 0.1203          | 0.94     |
  | 0.1912        | 1.41  | 2200 | 0.1037          | 0.94     |
  | 0.1614        | 1.44  | 2250 | 0.1006          | 0.9533   |
  | 0.1975        | 1.47  | 2300 | 0.0985          | 0.9533   |
  | 0.1843        | 1.5   | 2350 | 0.0922          | 0.9533   |
  | 0.1764        | 1.54  | 2400 | 0.1259          | 0.9467   |
  | 0.1855        | 1.57  | 2450 | 0.1243          | 0.96     |
  | 0.1272        | 1.6   | 2500 | 0.2107          | 0.9267   |
  | 0.241         | 1.63  | 2550 | 0.1142          | 0.9533   |
  | 0.1584        | 1.66  | 2600 | 0.1194          | 0.9467   |
  | 0.1568        | 1.7   | 2650 | 0.1196          | 0.9533   |
  | 0.1896        | 1.73  | 2700 | 0.1311          | 0.9533   |
  | 0.143         | 1.76  | 2750 | 0.1140          | 0.9533   |
  | 0.227         | 1.79  | 2800 | 0.1482          | 0.9333   |
  | 0.1404        | 1.82  | 2850 | 0.1366          | 0.94     |
  | 0.1865        | 1.86