readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: hsohn3/mayo-timebert-visit-uncased-wordlevel-block512-batch4-ep100
    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. -->
  
  # hsohn3/mayo-timebert-visit-uncased-wordlevel-block512-batch4-ep100
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.8536
  - 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Epoch |
  |:----------:|:-----:|
  | 3.9508     | 0     |
  | 3.4063     | 1     |
  | 3.3682     | 2     |
  | 3.3468     | 3     |
  | 3.3330     | 4     |
  | 3.3308     | 5     |
  | 3.3225     | 6     |
  | 3.3106     | 7     |
  | 3.2518     | 8     |
  | 3.1859     | 9     |
  | 3.1373     | 10    |
  | 3.0923     | 11    |
  | 3.0390     | 12    |
  | 2.9560     | 13    |
  | 2.8605     | 14    |
  | 2.7564     | 15    |
  | 2.4969     | 16    |
  | 2.2044     | 17    |
  | 1.9566     | 18    |
  | 1.7686     | 19    |
  | 1.5995     | 20    |
  | 1.4932     | 21    |
  | 1.4100     | 22    |
  | 1.3538     | 23    |
  | 1.2973     | 24    |
  | 1.2610     | 25    |
  | 1.2160     | 26    |
  | 1.1916     | 27    |
  | 1.1607     | 28    |
  | 1.1468     | 29    |
  | 1.1262     | 30    |
  | 1.1123     | 31    |
  | 1.0942     | 32    |
  | 1.0816     | 33    |
  | 1.0717     | 34    |
  | 1.0575     | 35    |
  | 1.0503     | 36    |
  | 1.0411     | 37    |
  | 1.0293     | 38    |
  | 1.0229     | 39    |
  | 1.0139     | 40    |
  | 1.0081     | 41    |
  | 1.0028     | 42    |
  | 0.9967     | 43    |
  | 0.9906     | 44    |
  | 0.9834     | 45    |
  | 0.9782     | 46    |
  | 0.9766     | 47    |
  | 0.9676     | 48    |
  | 0.9618     | 49    |
  | 0.9611     | 50    |
  | 0.9553     | 51    |
  | 0.9504     | 52    |
  | 0.9483     | 53    |
  | 0.9404     | 54    |
  | 0.9423     | 55    |
  | 0.9361     | 56    |
  | 0.9327     | 57    |
  | 0.9327     | 58    |
  | 0.9263     | 59    |
  | 0.9275     | 60    |
  | 0.9218     | 61    |
  | 0.9202     | 62    |
  | 0.9158     | 63    |
  | 0.9152     | 64    |
  | 0.9091     | 65    |
  | 0.9104     | 66    |
  | 0.9094     | 67    |
  | 0.9087     | 68    |
  | 0.9034     | 69    |
  | 0.9063     | 70    |
  | 0.8984     | 71    |
  | 0.8966     | 72    |
  | 0.8953     | 73    |
  | 0.8910     | 74    |
  | 0.8913     | 75    |
  | 0.8887     | 76    |
  | 0.8868     | 77    |
  | 0.8868     | 78    |
  | 0.8815     | 79    |
  | 0.8821     | 80    |
  | 0.8791     | 81    |
  | 0.8752     | 82    |
  | 0.8731     | 83    |
  | 0.8779     | 84    |
  | 0.8727     | 85    |
  | 0.8702     | 86    |
  | 0.8712     | 87    |
  | 0.8689     | 88    |
  | 0.8646     | 89    |
  | 0.8644     | 90    |
  | 0.8608     | 91    |
  | 0.8643     | 92    |
  | 0.8602     | 93    |
  | 0.8605     | 94    |
  | 0.8568     | 95    |
  | 0.8567     | 96    |
  | 0.8557     | 97    |
  | 0.8543     | 98    |
  | 0.8536     | 99    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.8.2
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  