readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: BERT_MC_OpenBookQA_from_scratch
    results: []
  ---
  
  <!-- 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. -->
  
  # BERT_MC_OpenBookQA_from_scratch
  
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3863
  - Accuracy: 0.268
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1000
  
  ### Training results
  
  | Training Loss | Epoch  | Step   | Validation Loss | Accuracy |
  |:-------------:|:------:|:------:|:---------------:|:--------:|
  | No log        | 1.0    | 310    | 1.2995          | 0.366    |
  | 1.206         | 2.0    | 620    | 1.2607          | 0.462    |
  | 1.206         | 3.0    | 930    | 1.2848          | 0.474    |
  | 0.9058        | 4.0    | 1240   | 1.6050          | 0.472    |
  | 0.6435        | 5.0    | 1550   | 1.5843          | 0.47     |
  | 0.6435        | 6.0    | 1860   | 2.1529          | 0.452    |
  | 0.444         | 7.0    | 2170   | 2.7774          | 0.444    |
  | 0.444         | 8.0    | 2480   | 2.0983          | 0.454    |
  | 0.3005        | 9.0    | 2790   | 2.8257          | 0.46     |
  | 0.1875        | 10.0   | 3100   | 4.0687          | 0.45     |
  | 0.1875        | 11.0   | 3410   | 4.8267          | 0.424    |
  | 0.1508        | 12.0   | 3720   | 4.2751          | 0.426    |
  | 0.1015        | 13.0   | 4030   | 5.0416          | 0.44     |
  | 0.1015        | 14.0   | 4340   | 6.0999          | 0.436    |
  | 0.0758        | 15.0   | 4650   | 5.8698          | 0.44     |
  | 0.0758        | 16.0   | 4960   | 4.6333          | 0.426    |
  | 0.0609        | 17.0   | 5270   | 6.0075          | 0.398    |
  | 0.0415        | 18.0   | 5580   | 6.3479          | 0.392    |
  | 0.0415        | 19.0   | 5890   | 5.7519          | 0.412    |
  | 0.0451        | 20.0   | 6200   | 6.7130          | 0.412    |
  | 0.0273        | 21.0   | 6510   | 5.2695          | 0.414    |
  | 0.0273        | 22.0   | 6820   | 7.4730          | 0.414    |
  | 0.0288        | 23.0   | 7130   | 5.4541          | 0.42     |
  | 0.0288        | 24.0   | 7440   | 6.4990          | 0.418    |
  | 0.0211        | 25.0   | 7750   | 8.1350          | 0.428    |
  | 0.0276        | 26.0   | 8060   | 7.2577          | 0.41     |
  | 0.0276        | 27.0   | 8370   | 4.0796          | 0.232    |
  | 0.3193        | 28.0   | 8680   | 5.9266          | 0.412    |
  | 0.3193        | 29.0   | 8990   | 7.7326          | 0.396    |
  | 0.34          | 30.0   | 9300   | 5.6181          | 0.418    |
  | 0.0298        | 31.0   | 9610   | 8.2390          | 0.43     |
  | 0.0298        | 32.0   | 9920   | 7.7127          | 0.408    |
  | 0.039         | 33.0   | 10230  | 5.9863          | 0.438    |
  | 0.0262        | 34.0   | 10540  | 7.2023          | 0.44     |
  | 0.0262        | 35.0   | 10850  | 7.0562          | 0.43     |
  | 0.0136        | 36.0   | 11160  | 8.2601          | 0.426    |
  | 0.0136        | 37.0   | 11470  | 7.8976          | 0.428    |
  | 0.0104        | 38.0   | 11780  | 6.1737          | 0.428    |
  | 0.0094        | 39.0   | 12090  | 7.8364          | 0.42     |
  | 0.0094        | 40.0   | 12400  | 6.5378          | 0.43     |
  | 0.099         | 41.0   | 12710  | 6.8616          | 0.412    |
  | 0.0195        | 42.0   | 13020  | 7.3664          | 0.418    |
  | 0.0195        | 43.0   | 13330  | 7.5156          | 0.416    |
  | 0.0145        | 44.0   | 13640  | 7.0715          | 0.408    |
  | 0.0145        | 45.0   | 13950  | 8.1128          | 0.41     |
  | 0.0143        | 46.0   | 14260  | 8.5357          | 0.424    |
  | 0.0126        | 47.0   | 14570  | 8.8933          | 0.412    |
  | 0.0126        | 48.0   | 14880  | 6.4196          | 0.42     |
  | 0.0073        | 49.0   | 15190  | 6.6502          | 0.402    |
  | 0.0314        | 50.0   | 15500  | 6.1884          | 0.368    |
  | 0.0314        | 51.0   | 15810  | 8.1288          | 0.392    |
  | 0.0544        | 52.0   | 16120  | 5.5377          | 0.372    |
  | 0.0544        | 53.0   | 16430  | 6.7587          | 0.402    |
  | 0.0366        | 54.0   | 16740  | 6.8984          | 0.396    |
  | 0.0168        | 55.0   | 17050  | 6.9548          | 0.398    |
  | 0.0168        | 56.0   | 17360  | 8.0131          | 0.402    |
  | 0.0117        | 57.0   | 17670  | 8.2451          | 0.412    |
  | 0.0117        | 58.0   | 17980  | 6.8791          | 0.4      |
  | 0.0077        | 59.0   | 18290  | 7.4470          | 0.388    |
  | 0.0194        | 60.0   