t5-small-summarize-billsum
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3984
- Rouge1: 0.2025
- Rouge2: 0.0983
- Rougel: 0.1707
- Rougelsum: 0.1707
- Gen Len: 20.0
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 124 | 2.8492 | 0.13 | 0.0388 | 0.1087 | 0.1089 | 20.0 |
| No log | 2.0 | 248 | 2.6212 | 0.1398 | 0.0499 | 0.1155 | 0.1152 | 20.0 |
| No log | 3.0 | 372 | 2.5327 | 0.148 | 0.0567 | 0.1237 | 0.1235 | 20.0 |
| No log | 4.0 | 496 | 2.4869 | 0.1627 | 0.0672 | 0.1345 | 0.1343 | 20.0 |
| 3.0124 | 5.0 | 620 | 2.4531 | 0.1842 | 0.0819 | 0.152 | 0.1518 | 20.0 |
| 3.0124 | 6.0 | 744 | 2.4297 | 0.194 | 0.088 | 0.1616 | 0.1617 | 20.0 |
| 3.0124 | 7.0 | 868 | 2.4147 | 0.1981 | 0.0934 | 0.1666 | 0.1665 | 20.0 |
| 3.0124 | 8.0 | 992 | 2.4061 | 0.2022 | 0.098 | 0.1705 | 0.1705 | 20.0 |
| 2.6076 | 9.0 | 1116 | 2.4001 | 0.2025 | 0.0983 | 0.1707 | 0.1707 | 20.0 |
| 2.6076 | 10.0 | 1240 | 2.3984 | 0.2025 | 0.0983 | 0.1707 | 0.1707 | 20.0 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4