readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - amazon_polarity
  metrics:
  - accuracy
  model-index:
  - name: amazonPolarity_DistilBERT_5EE
    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: 0.94
  ---
  
  <!-- 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. -->
  
  # amazonPolarity_DistilBERT_5EE
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the amazon_polarity dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2899
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6581        | 0.03  | 50   | 0.5315          | 0.84     |
  | 0.4321        | 0.05  | 100  | 0.2897          | 0.8933   |
  | 0.298         | 0.08  | 150  | 0.3165          | 0.8667   |
  | 0.2902        | 0.11  | 200  | 0.2552          | 0.9067   |
  | 0.2824        | 0.13  | 250  | 0.2277          | 0.9133   |
  | 0.2522        | 0.16  | 300  | 0.1998          | 0.94     |
  | 0.2781        | 0.19  | 350  | 0.1933          | 0.94     |
  | 0.2668        | 0.21  | 400  | 0.2316          | 0.92     |
  | 0.2619        | 0.24  | 450  | 0.1968          | 0.9333   |
  | 0.2446        | 0.27  | 500  | 0.1846          | 0.9467   |
  | 0.2677        | 0.29  | 550  | 0.1818          | 0.94     |
  | 0.2026        | 0.32  | 600  | 0.2348          | 0.9133   |
  | 0.2351        | 0.35  | 650  | 0.2127          | 0.92     |
  | 0.2685        | 0.37  | 700  | 0.1792          | 0.94     |
  | 0.2141        | 0.4   | 750  | 0.2252          | 0.9133   |
  | 0.2193        | 0.43  | 800  | 0.2131          | 0.9267   |
  | 0.2456        | 0.45  | 850  | 0.2205          | 0.9133   |
  | 0.2548        | 0.48  | 900  | 0.1788          | 0.94     |
  | 0.2353        | 0.51  | 950  | 0.1954          | 0.9267   |
  | 0.2546        | 0.53  | 1000 | 0.1815          | 0.9333   |
  | 0.2583        | 0.56  | 1050 | 0.1654          | 0.9333   |
  | 0.219         | 0.59  | 1100 | 0.1760          | 0.9467   |
  | 0.2241        | 0.61  | 1150 | 0.2107          | 0.92     |
  | 0.2201        | 0.64  | 1200 | 0.2381          | 0.8933   |
  | 0.1745        | 0.67  | 1250 | 0.1944          | 0.92     |
  | 0.2698        | 0.69  | 1300 | 0.1971          | 0.9267   |
  | 0.214         | 0.72  | 1350 | 0.1944          | 0.9333   |
  | 0.2436        | 0.75  | 1400 | 0.2079          | 0.92     |
  | 0.2318        | 0.77  | 1450 | 0.2088          | 0.9333   |
  | 0.2206        | 0.8   | 1500 | 0.1875          | 0.94     |
  | 0.2593        | 0.83  | 1550 | 0.1797          | 0.9267   |
  | 0.1908        | 0.85  | 1600 | 0.1924          | 0.9333   |
  | 0.2378        | 0.88  | 1650 | 0.1649          | 0.9267   |
  | 0.2332        | 0.91  | 1700 | 0.1768          | 0.94     |
  | 0.2125        | 0.93  | 1750 | 0.2276          | 0.92     |
  | 0.2174        | 0.96  | 1800 | 0.2035          | 0.9333   |
  | 0.19          | 0.99  | 1850 | 0.1805          | 0.94     |
  | 0.1515        | 1.01  | 1900 | 0.1832          | 0.94     |
  | 0.1671        | 1.04  | 1950 | 0.1902          | 0.94     |
  | 0.171         | 1.07  | 2000 | 0.2468          | 0.9267   |
  | 0.1495        | 1.09  | 2050 | 0.2276          | 0.9267   |
  | 0.1535        | 1.12  | 2100 | 0.1926          | 0.94     |
  | 0.2085        | 1.15  | 2150 | 0.1878          | 0.94     |
  | 0.1395        | 1.17  | 2200 | 0.1795          | 0.9467   |
  | 0.1556        | 1.2   | 2250 | 0.1554          | 0.9467   |
  | 0.1273        | 1.23  | 2300 | 0.1707          | 0.94     |
  | 0.1873        | 1.25  | 2350 | 0.1867          | 0.9467   |
  | 0.1589        | 1.28  | 2400 | 0.2089          | 0.9333   |
  | 0.1426        | 1.31  | 2450 | 0.1797          | 0.9467   |
  | 0.149         | 1.33  | 2500 | 0.1991          | 0.9333   |
  | 0.1535        | 1.36  | 2550 | 0.2116          | 0.94     |
  | 0.1671        | 1.39  | 2600 | 0.1704          | 0.9467   |
  | 0.1582        | 1.41  | 2650 | 0.1843          | 0.94     |
  | 0.1393        | 1.44  | 2700 | 0.1831          | 0.94     |
  | 0.1474        | 1.47  | 2750 | 0.1895          | 0.94     |
  | 0.203         | 1.49  | 2800 | 0.1843          | 0.9467   |
  | 0.1562  