readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: hsohn3/cchs-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/cchs-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: 0.8009
  - 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 |
  |:----------:|:-----:|
  | 3.8699     | 0     |
  | 3.1667     | 1     |
  | 3.1286     | 2     |
  | 3.1169     | 3     |
  | 3.1077     | 4     |
  | 3.0989     | 5     |
  | 3.0911     | 6     |
  | 3.0896     | 7     |
  | 3.0820     | 8     |
  | 3.0856     | 9     |
  | 3.0827     | 10    |
  | 3.0800     | 11    |
  | 3.0647     | 12    |
  | 3.0396     | 13    |
  | 3.0052     | 14    |
  | 2.9879     | 15    |
  | 2.9633     | 16    |
  | 2.9449     | 17    |
  | 2.9217     | 18    |
  | 2.8921     | 19    |
  | 2.8625     | 20    |
  | 2.8153     | 21    |
  | 2.7495     | 22    |
  | 2.6202     | 23    |
  | 2.3762     | 24    |
  | 2.1064     | 25    |
  | 1.8489     | 26    |
  | 1.6556     | 27    |
  | 1.5005     | 28    |
  | 1.4110     | 29    |
  | 1.3472     | 30    |
  | 1.2896     | 31    |
  | 1.2391     | 32    |
  | 1.2001     | 33    |
  | 1.1663     | 34    |
  | 1.1418     | 35    |
  | 1.1159     | 36    |
  | 1.0987     | 37    |
  | 1.0753     | 38    |
  | 1.0608     | 39    |
  | 1.0456     | 40    |
  | 1.0381     | 41    |
  | 1.0248     | 42    |
  | 1.0127     | 43    |
  | 0.9970     | 44    |
  | 0.9958     | 45    |
  | 0.9847     | 46    |
  | 0.9789     | 47    |
  | 0.9617     | 48    |
  | 0.9575     | 49    |
  | 0.9517     | 50    |
  | 0.9442     | 51    |
  | 0.9379     | 52    |
  | 0.9350     | 53    |
  | 0.9325     | 54    |
  | 0.9235     | 55    |
  | 0.9182     | 56    |
  | 0.9139     | 57    |
  | 0.9074     | 58    |
  | 0.8984     | 59    |
  | 0.8988     | 60    |
  | 0.8958     | 61    |
  | 0.8937     | 62    |
  | 0.8853     | 63    |
  | 0.8812     | 64    |
  | 0.8758     | 65    |
  | 0.8729     | 66    |
  | 0.8732     | 67    |
  | 0.8647     | 68    |
  | 0.8634     | 69    |
  | 0.8604     | 70    |
  | 0.8577     | 71    |
  | 0.8597     | 72    |
  | 0.8508     | 73    |
  | 0.8510     | 74    |
  | 0.8450     | 75    |
  | 0.8451     | 76    |
  | 0.8398     | 77    |
  | 0.8392     | 78    |
  | 0.8345     | 79    |
  | 0.8350     | 80    |
  | 0.8329     | 81    |
  | 0.8299     | 82    |
  | 0.8257     | 83    |
  | 0.8217     | 84    |
  | 0.8192     | 85    |
  | 0.8211     | 86    |
  | 0.8208     | 87    |
  | 0.8171     | 88    |
  | 0.8166     | 89    |
  | 0.8134     | 90    |
  | 0.8124     | 91    |
  | 0.8102     | 92    |
  | 0.8133     | 93    |
  | 0.8066     | 94    |
  | 0.8023     | 95    |
  | 0.8049     | 96    |
  | 0.8024     | 97    |
  | 0.7980     | 98    |
  | 0.8009     | 99    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.8.2
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  