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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
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