HealthScribe (A Clinical Note Generator)
This model is a fine-tuned version of facebook/bart-large-cnn on a modified version of MTS-Dialog Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.1562
- Rouge1: 54.3238
- Rouge2: 34.2678
- Rougel: 46.5847
- Rougelsum: 51.2214
- Gen Len: 77.04
Model description
More information neede
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.4426 | 1.0 | 600 | 0.1588 | 52.8864 | 33.253 | 44.9089 | 50.5072 | 69.38 |
| 0.1137 | 2.0 | 1201 | 0.1517 | 56.8499 | 35.309 | 48.2171 | 53.6983 | 72.74 |
| 0.0796 | 3.0 | 1800 | 0.1562 | 54.3238 | 34.2678 | 46.5847 | 51.2214 | 77.04 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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