readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: hsohn3/mayo-bert-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-bert-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: 0.9559
  - 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 |
  |:----------:|:-----:|
  | 4.1247     | 0     |
  | 3.5129     | 1     |
  | 3.4726     | 2     |
  | 3.4483     | 3     |
  | 3.4395     | 4     |
  | 3.4301     | 5     |
  | 3.4260     | 6     |
  | 3.4131     | 7     |
  | 3.3831     | 8     |
  | 3.2925     | 9     |
  | 3.2454     | 10    |
  | 3.2092     | 11    |
  | 3.1695     | 12    |
  | 3.1346     | 13    |
  | 3.0797     | 14    |
  | 3.0154     | 15    |
  | 2.9557     | 16    |
  | 2.8814     | 17    |
  | 2.7720     | 18    |
  | 2.5472     | 19    |
  | 2.3193     | 20    |
  | 2.1005     | 21    |
  | 1.9331     | 22    |
  | 1.7971     | 23    |
  | 1.6859     | 24    |
  | 1.6062     | 25    |
  | 1.5310     | 26    |
  | 1.4706     | 27    |
  | 1.4203     | 28    |
  | 1.3681     | 29    |
  | 1.3222     | 30    |
  | 1.2939     | 31    |
  | 1.2726     | 32    |
  | 1.2494     | 33    |
  | 1.2330     | 34    |
  | 1.2161     | 35    |
  | 1.1998     | 36    |
  | 1.1874     | 37    |
  | 1.1767     | 38    |
  | 1.1641     | 39    |
  | 1.1550     | 40    |
  | 1.1407     | 41    |
  | 1.1363     | 42    |
  | 1.1272     | 43    |
  | 1.1227     | 44    |
  | 1.1163     | 45    |
  | 1.1065     | 46    |
  | 1.1008     | 47    |
  | 1.0957     | 48    |
  | 1.0837     | 49    |
  | 1.0844     | 50    |
  | 1.0778     | 51    |
  | 1.0741     | 52    |
  | 1.0693     | 53    |
  | 1.0662     | 54    |
  | 1.0608     | 55    |
  | 1.0521     | 56    |
  | 1.0526     | 57    |
  | 1.0476     | 58    |
  | 1.0454     | 59    |
  | 1.0452     | 60    |
  | 1.0348     | 61    |
  | 1.0333     | 62    |
  | 1.0342     | 63    |
  | 1.0293     | 64    |
  | 1.0249     | 65    |
  | 1.0241     | 66    |
  | 1.0194     | 67    |
  | 1.0177     | 68    |
  | 1.0102     | 69    |
  | 1.0055     | 70    |
  | 1.0052     | 71    |
  | 1.0038     | 72    |
  | 1.0005     | 73    |
  | 0.9981     | 74    |
  | 0.9991     | 75    |
  | 0.9950     | 76    |
  | 0.9928     | 77    |
  | 0.9898     | 78    |
  | 0.9906     | 79    |
  | 0.9873     | 80    |
  | 0.9849     | 81    |
  | 0.9808     | 82    |
  | 0.9804     | 83    |
  | 0.9792     | 84    |
  | 0.9789     | 85    |
  | 0.9797     | 86    |
  | 0.9741     | 87    |
  | 0.9781     | 88    |
  | 0.9678     | 89    |
  | 0.9686     | 90    |
  | 0.9651     | 91    |
  | 0.9652     | 92    |
  | 0.9613     | 93    |
  | 0.9599     | 94    |
  | 0.9566     | 95    |
  | 0.9571     | 96    |
  | 0.9577     | 97    |
  | 0.9536     | 98    |
  | 0.9559     | 99    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.8.2
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  