metadata
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: PegasusMedicalSummary
results: []
PegasusMedicalSummary
Authors
This model was created by renegarza and mereshd.
This model is a fine-tuned version of google/pegasus-xsum on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1438
- Rouge1: 0.4318
- Rouge2: 0.2525
- Rougel: 0.3524
- Rougelsum: 0.3525
- Gen Len: 55.882
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|---|
| 6.5172 | 1.0 | 999 | 0.1784 | 0.4161 | 0.2373 | 0.3388 | 0.3384 | 52.102 |
| 0.3174 | 2.0 | 1999 | 0.1550 | 0.4236 | 0.2434 | 0.343 | 0.3428 | 54.458 |
| 0.2632 | 3.0 | 2999 | 0.1462 | 0.4269 | 0.2467 | 0.3465 | 0.3464 | 55.503 |
| 0.2477 | 4.0 | 3996 | 0.1438 | 0.4318 | 0.2525 | 0.3524 | 0.3525 | 55.882 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3