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medical_diagnostic_summarizer
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.1099
- Rouge1: 0.398
- Rouge2: 0.2035
- Rougel: 0.3373
- Rougelsum: 0.3373
- Gen Len: 17.8606
Model description
More information needed
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.4288 | 1.0 | 2500 | 2.1944 | 0.3895 | 0.1972 | 0.3304 | 0.3303 | 17.8459 |
| 2.3376 | 2.0 | 5000 | 2.1381 | 0.3948 | 0.2012 | 0.3347 | 0.3347 | 17.8277 |
| 2.2978 | 3.0 | 7500 | 2.1155 | 0.3972 | 0.2027 | 0.3365 | 0.3366 | 17.8694 |
| 2.3072 | 4.0 | 10000 | 2.1099 | 0.398 | 0.2035 | 0.3373 | 0.3373 | 17.8606 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
