readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: pretrained-bert-uncased-200
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # pretrained-bert-uncased-200
  
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: nan
  - Validation Loss: nan
  - Epoch: 199
  
  ## 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:
  - optimizer: {'name': 'Adam', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 8.9076     | 9.5544          | 0     |
  | 7.0572     | 9.6310          | 1     |
  | 6.5781     | 10.4973         | 2     |
  | 6.1054     | 10.4749         | 3     |
  | 6.1980     | 10.4411         | 4     |
  | 6.0896     | 11.1385         | 5     |
  | 6.1630     | 10.8668         | 6     |
  | 5.9313     | 11.2520         | 7     |
  | 5.7459     | 10.9396         | 8     |
  | 5.8505     | 11.1343         | 9     |
  | 5.8592     | 11.6048         | 10    |
  | 5.7595     | 12.0371         | 11    |
  | 5.7283     | 11.4402         | 12    |
  | 5.7948     | 11.6117         | 13    |
  | 5.7973     | 11.7393         | 14    |
  | 5.6228     | 11.9450         | 15    |
  | 5.6996     | 11.9938         | 16    |
  | 5.7468     | 12.3826         | 17    |
  | 5.6336     | 11.7692         | 18    |
  | 5.6287     | 12.1970         | 19    |
  | 5.7435     | 12.3895         | 20    |
  | 5.6587     | 12.2124         | 21    |
  | 5.6767     | 12.1633         | 22    |
  | 5.7494     | 12.1844         | 23    |
  | 5.5532     | 12.4163         | 24    |
  | 5.4826     | 12.3235         | 25    |
  | 5.7103     | 12.7326         | 26    |
  | 5.6399     | 12.3326         | 27    |
  | 5.6171     | 12.4726         | 28    |
  | 5.8517     | 12.3647         | 29    |
  | 5.6446     | 12.4943         | 30    |
  | 5.5662     | 12.6303         | 31    |
  | 5.8222     | 12.5869         | 32    |
  | 5.5710     | 13.0406         | 33    |
  | 5.6011     | 12.5007         | 34    |
  | 5.6860     | 12.2958         | 35    |
  | 5.6071     | 12.5690         | 36    |
  | 5.5824     | 12.4472         | 37    |
  | 5.5800     | 12.8570         | 38    |
  | 5.6298     | 12.9604         | 39    |
  | 5.4751     | 13.0937         | 40    |
  | 5.5724     | 12.8909         | 41    |
  | 5.6251     | 13.1132         | 42    |
  | 5.5483     | 12.7036         | 43    |
  | 5.6252     | 13.1233         | 44    |
  | 5.4592     | 13.1353         | 45    |
  | 5.5780     | 13.2373         | 46    |
  | 5.5350     | 13.4289         | 47    |
  | 5.4859     | 13.3994         | 48    |
  | 5.6908     | 13.1062         | 49    |
  | 5.7516     | 13.1705         | 50    |
  | 5.5373     | 13.3196         | 51    |
  | 5.6078     | 13.3352         | 52    |
  | 5.5998     | 13.3831         | 53    |
  | 5.6833     | 13.4430         | 54    |
  | 5.6047     | 12.7287         | 55    |
  | 5.7165     | 13.1647         | 56    |
  | 5.5246     | 13.5831         | 57    |
  | 5.5244     | 13.4733         | 58    |
  | 5.5659     | 13.8621         | 59    |
  | 5.6702     | 13.0873         | 60    |
  | 5.5403     | 13.2744         | 61    |
  | 5.4980     | 13.5826         | 62    |
  | 5.5052     | 13.4584         | 63    |
  | 5.5921     | 13.6191         | 64    |
  | 5.5647     | 13.2221         | 65    |
  | 5.6330     | 13.4804         | 66    |
  | 5.6607     | 13.0722         | 67    |
  | 5.7957     | 13.6183         | 68    |
  | 5.7403     | 13.5204         | 69    |
  | 5.5702     | 13.4229         | 70    |
  | 5.4891     | 13.6547         | 71    |
  | 5.7374     | 13.5464         | 72    |
  | 5.6032     | 13.3607         | 73    |
  | 5.5891     | 14.0467         | 74    |
  | 5.7014     | 13.7621         | 75    |
  | 5.6749     | 13.4568         | 76    |
  | 5.6180     | 13.7552         | 77    |
  | 5.6203     | 13.7563         | 78    |
  | 5.6290     | 13.4801         | 79    |
  | 5.6179     | 13.6345         | 80    |
  | 5.5856     | 13.8037         | 81    |
  | 5.6667     | 14.1205         | 82    |
  | 5.5012     | 14.2115         | 83    |
  | 5.6736     | 13.9032         | 84    |
  | 5.6132     | 13.7493         | 85    |
  | 5.6931     | 13.5402         | 86    |
  | 5.4744     | 13.9974         | 87    |
  | 5.6554     | 14.0855         | 88    |
  | 5.5775     | 13.7100         | 89    |
  | 5.6002     | 13.7944         | 90    |
  | 5.6341     | 14.4328         | 91    |
  | nan        | nan             | 92    |
  | nan        | nan             | 93    |
  | nan        | nan             | 94    |
  | nan        | nan             | 95   