t5summarization
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.4353
- Rouge1: 0.1862
- Rouge2: 0.0831
- Rougel: 0.1565
- Rougelsum: 0.1562
- Gen Len: 19.0
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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.5150 | 0.1469 | 0.0544 | 0.1214 | 0.1216 | 19.0 |
| No log | 2.0 | 124 | 2.4668 | 0.1659 | 0.0671 | 0.1369 | 0.1369 | 19.0 |
| No log | 3.0 | 186 | 2.4418 | 0.1801 | 0.0793 | 0.1515 | 0.1513 | 19.0 |
| No log | 4.0 | 248 | 2.4353 | 0.1862 | 0.0831 | 0.1565 | 0.1562 | 19.0 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3