readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: hsohn3/ehr-bert-base-uncased-cchs-wordlevel
    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/ehr-bert-base-uncased-cchs-wordlevel
  
  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: 3.7374
  - Epoch: 9
  
  ## Model description
  
  - model: bert-base-uncased (train from scratch)
  - tokenizer: BertTokenizer + WordLevel splitter
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  - data_source: cchs (10,000 visits)
  - data_format: visit-level texts concatenated by `[SEP]` token
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  - training_precision: float32
  - block_size: 512
  - batch_size: 4
  - num_epochs: 10
  - mlm_probability: 0.15
  
  ### Training results
  
  | Train Loss | Epoch |
  |:----------:|:-----:|
  | 3.8857     | 0     |
  | 3.7525     | 1     |
  | 3.7505     | 2     |
  | 3.7493     | 3     |
  | 3.7412     | 4     |
  | 3.7432     | 5     |
  | 3.7428     | 6     |
  | 3.7409     | 7     |
  | 3.7394     | 8     |
  | 3.7374     | 9     |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.8.2
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  