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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: deberta-pretrained-large
results: []
---
# Austin MeDeBERTa
This model was developed using further MLM pre-training on [microsoft/deberta-base](https://huggingface.co/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
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