readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: hsohn3/cchs-bert-visit-uncased-wordlevel-block512-batch4-ep60
    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-ep60
  
  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: 0.8314
  - Epoch: 59
  
  ## 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 |
  |:----------:|:-----:|
  | 3.8539     | 0     |
  | 3.0645     | 1     |
  | 3.0225     | 2     |
  | 3.0128     | 3     |
  | 3.0023     | 4     |
  | 2.9834     | 5     |
  | 2.9859     | 6     |
  | 2.9814     | 7     |
  | 2.9729     | 8     |
  | 2.9736     | 9     |
  | 2.9687     | 10    |
  | 2.9665     | 11    |
  | 2.9673     | 12    |
  | 2.9612     | 13    |
  | 2.9056     | 14    |
  | 2.8781     | 15    |
  | 2.8612     | 16    |
  | 2.8259     | 17    |
  | 2.8089     | 18    |
  | 2.7865     | 19    |
  | 2.7697     | 20    |
  | 2.7307     | 21    |
  | 2.6828     | 22    |
  | 2.6168     | 23    |
  | 2.5259     | 24    |
  | 2.3860     | 25    |
  | 2.2088     | 26    |
  | 2.0192     | 27    |
  | 1.8022     | 28    |
  | 1.5856     | 29    |
  | 1.4330     | 30    |
  | 1.3441     | 31    |
  | 1.2728     | 32    |
  | 1.2154     | 33    |
  | 1.1757     | 34    |
  | 1.1411     | 35    |
  | 1.1037     | 36    |
  | 1.0883     | 37    |
  | 1.0633     | 38    |
  | 1.0368     | 39    |
  | 1.0205     | 40    |
  | 1.0047     | 41    |
  | 0.9884     | 42    |
  | 0.9754     | 43    |
  | 0.9566     | 44    |
  | 0.9427     | 45    |
  | 0.9385     | 46    |
  | 0.9246     | 47    |
  | 0.9114     | 48    |
  | 0.9029     | 49    |
  | 0.8993     | 50    |
  | 0.8850     | 51    |
  | 0.8768     | 52    |
  | 0.8701     | 53    |
  | 0.8626     | 54    |
  | 0.8580     | 55    |
  | 0.8489     | 56    |
  | 0.8407     | 57    |
  | 0.8338     | 58    |
  | 0.8314     | 59    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.8.2
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  