t5-small-billsum
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9564
- Rouge1: 50.3551
- Rouge2: 29.3717
- Rougel: 39.4102
- Rougelsum: 43.6247
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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.5468 | 1.0 | 1185 | 2.0937 | 48.625 | 27.492 | 37.671 | 41.4628 |
| 2.2867 | 2.0 | 2370 | 2.0155 | 49.2547 | 28.248 | 38.39 | 42.3374 |
| 2.2241 | 3.0 | 3555 | 1.9796 | 49.8802 | 28.8333 | 38.8829 | 43.027 |
| 2.1925 | 4.0 | 4740 | 1.9620 | 50.07 | 28.9961 | 39.1086 | 43.3251 |
| 2.1791 | 5.0 | 5925 | 1.9576 | 50.2626 | 29.1819 | 39.2415 | 43.4781 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1