readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: hsohn3/cchs-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/cchs-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: 0.7195
  - 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 |
  |:----------:|:-----:|
  | 3.8730     | 0     |
  | 3.0562     | 1     |
  | 3.0168     | 2     |
  | 3.0032     | 3     |
  | 2.9954     | 4     |
  | 2.9951     | 5     |
  | 2.9904     | 6     |
  | 2.9765     | 7     |
  | 2.9788     | 8     |
  | 2.9692     | 9     |
  | 2.9656     | 10    |
  | 2.9761     | 11    |
  | 2.9643     | 12    |
  | 2.9393     | 13    |
  | 2.9026     | 14    |
  | 2.8685     | 15    |
  | 2.8438     | 16    |
  | 2.8279     | 17    |
  | 2.8107     | 18    |
  | 2.7896     | 19    |
  | 2.7716     | 20    |
  | 2.7458     | 21    |
  | 2.7118     | 22    |
  | 2.6519     | 23    |
  | 2.5933     | 24    |
  | 2.4702     | 25    |
  | 2.2842     | 26    |
  | 2.0712     | 27    |
  | 1.8406     | 28    |
  | 1.6374     | 29    |
  | 1.4836     | 30    |
  | 1.3824     | 31    |
  | 1.3079     | 32    |
  | 1.2538     | 33    |
  | 1.2054     | 34    |
  | 1.1700     | 35    |
  | 1.1432     | 36    |
  | 1.1122     | 37    |
  | 1.0939     | 38    |
  | 1.0645     | 39    |
  | 1.0465     | 40    |
  | 1.0248     | 41    |
  | 1.0069     | 42    |
  | 0.9902     | 43    |
  | 0.9769     | 44    |
  | 0.9510     | 45    |
  | 0.9394     | 46    |
  | 0.9316     | 47    |
  | 0.9181     | 48    |
  | 0.9090     | 49    |
  | 0.9010     | 50    |
  | 0.8934     | 51    |
  | 0.8791     | 52    |
  | 0.8759     | 53    |
  | 0.8652     | 54    |
  | 0.8566     | 55    |
  | 0.8511     | 56    |
  | 0.8414     | 57    |
  | 0.8373     | 58    |
  | 0.8302     | 59    |
  | 0.8241     | 60    |
  | 0.8246     | 61    |
  | 0.8207     | 62    |
  | 0.8110     | 63    |
  | 0.8081     | 64    |
  | 0.8010     | 65    |
  | 0.7995     | 66    |
  | 0.7965     | 67    |
  | 0.7941     | 68    |
  | 0.7849     | 69    |
  | 0.7866     | 70    |
  | 0.7874     | 71    |
  | 0.7796     | 72    |
  | 0.7742     | 73    |
  | 0.7706     | 74    |
  | 0.7687     | 75    |
  | 0.7686     | 76    |
  | 0.7663     | 77    |
  | 0.7586     | 78    |
  | 0.7554     | 79    |
  | 0.7563     | 80    |
  | 0.7541     | 81    |
  | 0.7527     | 82    |
  | 0.7482     | 83    |
  | 0.7460     | 84    |
  | 0.7436     | 85    |
  | 0.7423     | 86    |
  | 0.7422     | 87    |
  | 0.7385     | 88    |
  | 0.7367     | 89    |
  | 0.7321     | 90    |
  | 0.7320     | 91    |
  | 0.7354     | 92    |
  | 0.7271     | 93    |
  | 0.7270     | 94    |
  | 0.7210     | 95    |
  | 0.7236     | 96    |
  | 0.7263     | 97    |
  | 0.7237     | 98    |
  | 0.7195     | 99    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.8.2
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  