readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: pretrained-bert-uncased-100
    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-100
  
  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: 99
  
  ## 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 |
  |:----------:|:---------------:|:-----:|
  | 8.9143     | 9.5645          | 0     |
  | 7.0594     | 9.6348          | 1     |
  | 6.5846     | 10.4810         | 2     |
  | 6.1703     | 10.3871         | 3     |
  | 6.2204     | 10.4579         | 4     |
  | 5.9912     | 11.0864         | 5     |
  | 6.1670     | 10.8475         | 6     |
  | 5.9434     | 11.3010         | 7     |
  | 5.7437     | 10.9369         | 8     |
  | 5.8586     | 11.1204         | 9     |
  | 5.8595     | 11.5750         | 10    |
  | 5.7608     | 12.0360         | 11    |
  | 5.7219     | 11.4627         | 12    |
  | 5.8005     | 11.6418         | 13    |
  | 5.8040     | 11.7480         | 14    |
  | 5.6217     | 11.9184         | 15    |
  | 5.7095     | 11.9534         | 16    |
  | 5.7426     | 12.3718         | 17    |
  | 5.6365     | 11.7388         | 18    |
  | 5.6291     | 12.1911         | 19    |
  | 5.7437     | 12.3435         | 20    |
  | 5.6589     | 12.1656         | 21    |
  | 5.6835     | 12.1785         | 22    |
  | 5.7466     | 12.1934         | 23    |
  | 5.5470     | 12.4191         | 24    |
  | 5.4824     | 12.3100         | 25    |
  | 5.7151     | 12.7568         | 26    |
  | 5.6431     | 12.3509         | 27    |
  | 5.6188     | 12.4724         | 28    |
  | 5.8535     | 12.3254         | 29    |
  | 5.6457     | 12.5312         | 30    |
  | 5.5622     | 12.6608         | 31    |
  | 5.8279     | 12.6227         | 32    |
  | 5.5720     | 13.0677         | 33    |
  | 5.6025     | 12.5078         | 34    |
  | 5.6830     | 12.2650         | 35    |
  | 5.6089     | 12.5420         | 36    |
  | 5.5842     | 12.4246         | 37    |
  | 5.5823     | 12.8527         | 38    |
  | 5.6300     | 12.9306         | 39    |
  | 5.4753     | 13.0506         | 40    |
  | 5.5736     | 12.8653         | 41    |
  | 5.6237     | 13.1275         | 42    |
  | 5.5517     | 12.6621         | 43    |
  | 5.6275     | 13.0830         | 44    |
  | 5.4596     | 13.0334         | 45    |
  | 5.5789     | 13.1859         | 46    |
  | 5.5381     | 13.4193         | 47    |
  | 5.4859     | 13.3659         | 48    |
  | 5.6895     | 13.1080         | 49    |
  | 5.7514     | 13.1102         | 50    |
  | 5.5406     | 13.3108         | 51    |
  | 5.6091     | 13.3639         | 52    |
  | 5.5978     | 13.3497         | 53    |
  | 5.6819     | 13.3768         | 54    |
  | 5.6097     | 12.7091         | 55    |
  | 5.7161     | 13.1289         | 56    |
  | 5.5263     | 13.5468         | 57    |
  | 5.5250     | 13.4408         | 58    |
  | 5.5677     | 13.7557         | 59    |
  | 5.6698     | 13.0456         | 60    |
  | 5.5404     | 13.2635         | 61    |
  | 5.5019     | 13.5839         | 62    |
  | 5.5027     | 13.3752         | 63    |
  | 5.5898     | 13.5648         | 64    |
  | 5.5646     | 13.1321         | 65    |
  | 5.6336     | 13.4493         | 66    |
  | 5.6596     | 13.0167         | 67    |
  | 5.7952     | 13.6155         | 68    |
  | 5.7404     | 13.4588         | 69    |
  | 5.5704     | 13.3443         | 70    |
  | 5.4927     | 13.6466         | 71    |
  | 5.7395     | 13.6197         | 72    |
  | 5.5994     | 13.3629         | 73    |
  | 5.5902     | 14.0645         | 74    |
  | 5.7020     | 13.7721         | 75    |
  | 5.6767     | 13.4775         | 76    |
  | 5.6172     | 13.7838         | 77    |
  | 5.6232     | 13.7676         | 78    |
  | 5.6285     | 13.4416         | 79    |
  | 5.6174     | 13.5767         | 80    |
  | 5.5878     | 13.7731         | 81    |
  | 5.6670     | 14.1654         | 82    |
  | 5.5013     | 14.2273         | 83    |
  | 5.6745     | 13.9600         | 84    |
  | 5.6135     | 13.8017         | 85    |
  | 5.6932     | 13.6257         | 86    |
  | 5.4745     | 13.9570         | 87    |
  | 5.6542     | 14.0449         | 88    |
  | 5.5748     | 13.6820         | 89    |
  | 5.6025     | 13.7910         | 90    |
  | 5.6333     | 14.4047         | 91    |
  | nan        | nan             | 92    |
  | nan        | nan             | 93    |
  | nan        | nan             | 94    |
  | nan        | nan             | 95    