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hsohn3/ehr-bert-base-uncased-cchs-wordlevel
This model is a fine-tuned version of 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
