Austin MeDeBERTa
This model was developed using further MLM pre-training on microsoft/deberta-base, using a dataset of 1.1M clinical notes from the Austin Health EMR. The notes span discharge summaries, inpatient notes, radiology reports and histopathology reports.
Model description
This is the base version of the original DeBERTa model. The architecture and tokenizer are unchanged.
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9756 | 0.51 | 40000 | 0.9127 |
| 0.8876 | 1.01 | 80000 | 0.8221 |
| 0.818 | 1.52 | 120000 | 0.7786 |
| 0.7836 | 2.03 | 160000 | 0.7438 |
| 0.7672 | 2.54 | 200000 | 0.7165 |
| 0.734 | 3.04 | 240000 | 0.6948 |
| 0.7079 | 3.55 | 280000 | 0.6749 |
| 0.6987 | 4.06 | 320000 | 0.6598 |
| 0.6771 | 4.57 | 360000 | 0.6471 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.15.1
- Tokenizers 0.10.3
- Downloads last month
- 20
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.