readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: pretrained-m-bert-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-m-bert-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: 5.6892
  - Validation Loss: 15.9999
  - 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 |
  |:----------:|:---------------:|:-----:|
  | 10.2629    | 10.9400         | 0     |
  | 7.8719     | 10.8986         | 1     |
  | 6.8337     | 11.4901         | 2     |
  | 6.4663     | 11.6037         | 3     |
  | 6.4171     | 11.5051         | 4     |
  | 6.3166     | 12.1207         | 5     |
  | 6.4304     | 11.7927         | 6     |
  | 6.0435     | 12.1347         | 7     |
  | 5.9134     | 12.1229         | 8     |
  | 6.0124     | 12.0225         | 9     |
  | 5.9096     | 12.4855         | 10    |
  | 5.8829     | 12.7256         | 11    |
  | 5.8533     | 12.3504         | 12    |
  | 5.8075     | 12.7843         | 13    |
  | 6.0418     | 12.6493         | 14    |
  | 5.8611     | 12.4900         | 15    |
  | 5.8863     | 12.7790         | 16    |
  | 5.9484     | 13.0246         | 17    |
  | 5.8226     | 12.9865         | 18    |
  | 5.8262     | 13.1064         | 19    |
  | 5.8687     | 13.1811         | 20    |
  | 5.7531     | 13.2824         | 21    |
  | 5.8473     | 13.2894         | 22    |
  | 5.8762     | 13.1719         | 23    |
  | 5.7386     | 13.0748         | 24    |
  | 5.6647     | 13.3089         | 25    |
  | 5.8553     | 13.5698         | 26    |
  | 5.7698     | 14.1035         | 27    |
  | 5.7972     | 13.6096         | 28    |
  | 5.9381     | 13.1142         | 29    |
  | 5.8173     | 13.1007         | 30    |
  | 5.7676     | 13.6502         | 31    |
  | 5.9740     | 13.5317         | 32    |
  | 5.6842     | 13.7206         | 33    |
  | 5.7764     | 13.5819         | 34    |
  | 5.7659     | 13.4004         | 35    |
  | 5.7104     | 13.6715         | 36    |
  | 5.8345     | 13.5589         | 37    |
  | 5.8067     | 13.6957         | 38    |
  | 5.8537     | 13.6661         | 39    |
  | 5.6418     | 13.8966         | 40    |
  | 5.7818     | 13.7630         | 41    |
  | 5.7406     | 14.1682         | 42    |
  | 5.7053     | 13.8797         | 43    |
  | 5.7151     | 14.1307         | 44    |
  | 5.6621     | 14.1855         | 45    |
  | 5.6716     | 14.1013         | 46    |
  | 5.6596     | 14.2236         | 47    |
  | 5.6680     | 14.0390         | 48    |
  | 5.8122     | 14.0500         | 49    |
  | 5.8497     | 14.0991         | 50    |
  | 5.6758     | 14.5258         | 51    |
  | 5.7158     | 14.2373         | 52    |
  | 5.7288     | 13.9851         | 53    |
  | 5.9239     | 14.2297         | 54    |
  | 5.6722     | 13.6866         | 55    |
  | 5.8708     | 14.2755         | 56    |
  | 5.7190     | 14.4764         | 57    |
  | 5.7218     | 14.1861         | 58    |
  | 5.7478     | 14.3363         | 59    |
  | 5.7843     | 13.9645         | 60    |
  | 5.6555     | 14.1351         | 61    |
  | 5.6951     | 14.5155         | 62    |
  | 5.6711     | 14.4671         | 63    |
  | 5.7068     | 14.4064         | 64    |
  | 5.7773     | 14.5143         | 65    |
  | 5.7188     | 14.6878         | 66    |
  | 5.7912     | 14.3496         | 67    |
  | 5.9308     | 14.4187         | 68    |
  | 5.8765     | 14.6648         | 69    |
  | 5.7103     | 14.3686         | 70    |
  | 5.6585     | 14.3171         | 71    |
  | 5.8697     | 14.2778         | 72    |
  | 5.6874     | 14.1511         | 73    |
  | 5.7367     | 15.0222         | 74    |
  | 5.8603     | 14.2226         | 75    |
  | 5.8183     | 14.6257         | 76    |
  | 5.7646     | 14.5472         | 77    |
  | 5.7813     | 14.4560         | 78    |
  | 5.6991     | 14.1486         | 79    |
  | 5.7365     | 14.5998         | 80    |
  | 5.7602     | 14.3595         | 81    |
  | 5.7646     | 14.4916         | 82    |
  | 5.6289     | 15.1076         | 83    |
  | 5.8171     | 14.7216         | 84    |
  | 5.7939     | 14.9316         | 85    |
  | 5.8249     | 14.6632         | 86    |
  | 5.6479     | 15.2074         | 87    |
  | 5.7985     | 14.9238         | 88    |
  | 5.7332     | 14.4504         | 89    |
  | 5.7495     | 14.2924         | 90    |
  | 5.7579     | 15.3362         | 91    |
  | 5.7217     | 15.0819         | 92    |
  | 5.6750     | 14.9618         | 93    |
  | 5.8607     | 14.6850         | 94    |
  | 5.6310     | 14.9199         | 95    |
  | 