readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: pretrained-m-bert-400
    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-400
  
  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: 399
  
  ## 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 |
  |:----------:|:---------------:|:-----:|
  | 10.2737    | 10.9284         | 0     |
  | 7.7909     | 10.9299         | 1     |
  | 6.9555     | 11.4698         | 2     |
  | 6.4835     | 11.5760         | 3     |
  | 6.3613     | 11.4740         | 4     |
  | 6.3206     | 12.1134         | 5     |
  | 6.5777     | 11.8247         | 6     |
  | 6.0680     | 12.1764         | 7     |
  | 5.9353     | 12.1038         | 8     |
  | 6.0701     | 12.0687         | 9     |
  | 6.0047     | 12.4985         | 10    |
  | 5.9272     | 12.8107         | 11    |
  | 5.9446     | 12.5006         | 12    |
  | 5.9716     | 12.8384         | 13    |
  | 6.0548     | 12.3585         | 14    |
  | 5.8666     | 12.5273         | 15    |
  | 5.8951     | 12.8032         | 16    |
  | 5.9528     | 13.0296         | 17    |
  | 5.8313     | 12.9472         | 18    |
  | 5.8324     | 13.0546         | 19    |
  | 5.8763     | 13.1180         | 20    |
  | 5.7623     | 13.2588         | 21    |
  | 5.8636     | 13.2705         | 22    |
  | 5.8864     | 13.1756         | 23    |
  | 5.7413     | 13.0413         | 24    |
  | 5.6825     | 13.2796         | 25    |
  | 5.8705     | 13.5748         | 26    |
  | 5.7772     | 14.0853         | 27    |
  | 5.8029     | 13.5957         | 28    |
  | 5.9590     | 13.0809         | 29    |
  | 5.8240     | 13.0912         | 30    |
  | 5.7687     | 13.5828         | 31    |
  | 5.9836     | 13.5432         | 32    |
  | 5.6915     | 13.7082         | 33    |
  | 5.7853     | 13.6080         | 34    |
  | 5.7760     | 13.3992         | 35    |
  | 5.7134     | 13.6552         | 36    |
  | 5.8415     | 13.5479         | 37    |
  | 5.8087     | 13.6847         | 38    |
  | 5.8611     | 13.6231         | 39    |
  | 5.6492     | 13.8722         | 40    |
  | 5.7846     | 13.7056         | 41    |
  | 5.7455     | 14.1208         | 42    |
  | 5.7129     | 13.7774         | 43    |
  | 5.7185     | 14.0725         | 44    |
  | 5.6655     | 14.0980         | 45    |
  | 5.6734     | 14.0126         | 46    |
  | 5.6658     | 14.1982         | 47    |
  | 5.6720     | 14.0881         | 48    |
  | 5.8220     | 14.0841         | 49    |
  | 5.8567     | 14.0512         | 50    |
  | 5.6811     | 14.4002         | 51    |
  | 5.7271     | 14.1651         | 52    |
  | 5.7329     | 13.8948         | 53    |
  | 5.9306     | 14.1744         | 54    |
  | 5.6757     | 13.6761         | 55    |
  | 5.8785     | 14.1815         | 56    |
  | 5.7267     | 14.4592         | 57    |
  | 5.7313     | 14.1220         | 58    |
  | 5.7537     | 14.3197         | 59    |
  | 5.7907     | 13.9449         | 60    |
  | 5.6611     | 14.0992         | 61    |
  | 5.7009     | 14.4630         | 62    |
  | 5.6760     | 14.3946         | 63    |
  | 5.7096     | 14.2776         | 64    |
  | 5.7778     | 14.3569         | 65    |
  | 5.7223     | 14.5246         | 66    |
  | 5.7954     | 14.2003         | 67    |
  | 5.9369     | 14.3692         | 68    |
  | 5.8792     | 14.5358         | 69    |
  | 5.7172     | 14.3076         | 70    |
  | 5.6608     | 14.1833         | 71    |
  | 5.8710     | 14.1070         | 72    |
  | 5.6896     | 13.9720         | 73    |
  | 5.7404     | 14.8816         | 74    |
  | 5.8649     | 14.1338         | 75    |
  | 5.8223     | 14.4951         | 76    |
  | 5.7701     | 14.4468         | 77    |
  | 5.7852     | 14.3300         | 78    |
  | 5.7038     | 14.0439         | 79    |
  | 5.7386     | 14.3995         | 80    |
  | 5.7594     | 14.1541         | 81    |
  | 5.7688     | 14.3452         | 82    |
  | 5.6329     | 14.9077         | 83    |
  | 5.8224     | 14.5802         | 84    |
  | 5.7969     | 14.8311         | 85    |
  | 5.8297     | 14.5400         | 86    |
  | 5.6488     | 15.0369         | 87    |
  | 5.8020     | 14.7833         | 88    |
  | 5.7345     | 14.3675         | 89    |
  | 5.7530     | 14.1602         | 90    |
  | 5.7599     | 15.2734         | 91    |
  | 5.7256     | 14.9461         | 92    |
  | 5.6803     | 14.8461         | 93    |
  | 5.8602     | 14.5303         | 94    |
  | 5.6319     | 14.8087         | 95    |
  | 5.7581 