readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: pretrained-m-bert-500
    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-500
  
  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: 499
  
  ## 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 |
  |:----------:|:---------------:|:-----:|
  | 10.2739    | 10.9467         | 0     |
  | 7.7645     | 10.9288         | 1     |
  | 6.8555     | 11.5279         | 2     |
  | 6.4632     | 11.6263         | 3     |
  | 6.3355     | 11.4757         | 4     |
  | 6.3058     | 12.0991         | 5     |
  | 6.4287     | 11.7486         | 6     |
  | 6.0511     | 12.1714         | 7     |
  | 5.9225     | 12.1125         | 8     |
  | 6.0564     | 12.0840         | 9     |
  | 5.9826     | 12.5151         | 10    |
  | 5.9158     | 12.8370         | 11    |
  | 5.9259     | 12.4708         | 12    |
  | 5.9949     | 12.9119         | 13    |
  | 6.0393     | 12.3977         | 14    |
  | 5.8529     | 12.5782         | 15    |
  | 5.8925     | 12.8304         | 16    |
  | 5.9375     | 13.0765         | 17    |
  | 5.8301     | 12.9770         | 18    |
  | 5.8228     | 13.0910         | 19    |
  | 5.8745     | 13.1173         | 20    |
  | 5.7530     | 13.1872         | 21    |
  | 5.8580     | 13.2372         | 22    |
  | 5.8831     | 13.1819         | 23    |
  | 5.7337     | 13.0628         | 24    |
  | 5.6735     | 13.2866         | 25    |
  | 5.8513     | 13.4646         | 26    |
  | 5.7785     | 14.1611         | 27    |
  | 5.8023     | 13.6074         | 28    |
  | 5.9448     | 13.0115         | 29    |
  | 5.8186     | 13.0827         | 30    |
  | 5.7649     | 13.5381         | 31    |
  | 5.9589     | 13.5486         | 32    |
  | 5.6677     | 13.6187         | 33    |
  | 5.7742     | 13.5131         | 34    |
  | 5.7498     | 13.3843         | 35    |
  | 5.7025     | 13.6528         | 36    |
  | 5.8219     | 13.5450         | 37    |
  | 5.7838     | 13.7073         | 38    |
  | 5.8232     | 13.6628         | 39    |
  | 5.6149     | 13.8447         | 40    |
  | 5.7623     | 13.8217         | 41    |
  | 5.7256     | 14.2310         | 42    |
  | 5.6833     | 13.8236         | 43    |
  | 5.6959     | 14.1115         | 44    |
  | 5.6337     | 14.1601         | 45    |
  | 5.6291     | 14.0644         | 46    |
  | 5.6384     | 14.2376         | 47    |
  | 5.6432     | 14.0575         | 48    |
  | 5.7842     | 14.0357         | 49    |
  | 5.8243     | 14.0310         | 50    |
  | 5.6608     | 14.5138         | 51    |
  | 5.6837     | 14.3153         | 52    |
  | 5.6851     | 14.0351         | 53    |
  | 5.9102     | 14.3691         | 54    |
  | 5.6353     | 13.7349         | 55    |
  | 5.8288     | 14.1780         | 56    |
  | 5.6853     | 14.5344         | 57    |
  | 5.6768     | 14.1037         | 58    |
  | 5.7125     | 14.2650         | 59    |
  | 5.7264     | 13.9798         | 60    |
  | 5.6180     | 14.2999         | 61    |
  | 5.6552     | 14.6840         | 62    |
  | 5.5937     | 12.6319         | 63    |
  | 5.6968     | 14.4662         | 64    |
  | 5.7412     | 14.5146         | 65    |
  | 5.6894     | 14.7825         | 66    |
  | 5.7429     | 14.4179         | 67    |
  | 5.8970     | 14.5220         | 68    |
  | 5.8363     | 14.7431         | 69    |
  | 5.6723     | 14.3854         | 70    |
  | 5.6331     | 14.3606         | 71    |
  | 5.8211     | 14.2819         | 72    |
  | 5.6573     | 14.1377         | 73    |
  | 5.6679     | 15.0708         | 74    |
  | 5.8098     | 14.2208         | 75    |
  | 5.7651     | 14.5841         | 76    |
  | 5.7128     | 14.4615         | 77    |
  | 5.7240     | 14.3851         | 78    |
  | 5.6542     | 14.1252         | 79    |
  | 5.6956     | 14.5275         | 80    |
  | 5.7033     | 14.2555         | 81    |
  | 5.7193     | 14.5061         | 82    |
  | 5.5942     | 15.0025         | 83    |
  | 5.7616     | 14.7460         | 84    |
  | 5.7584     | 15.0039         | 85    |
  | 5.7949     | 14.6488         | 86    |
  | 5.6070     | 15.1781         | 87    |
  | 5.7464     | 14.9159         | 88    |
  | 5.6865     | 14.4204         | 89    |
  | 5.6934     | 14.2373         | 90    |
  | 5.7053     | 15.2664         | 91    |
  | 5.6629     | 15.0062         | 92    |
  | 5.6186     | 14.8861         | 93    |
  | 5.8011     | 14.5602         | 94    |
  | 5.5920     | 14.8159         | 95    |
  | 5.7014 