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summarization_model
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1359
- Rouge1: 0.1813
- Rouge2: 0.1114
- Rougel: 0.1616
- Rougelsum: 0.1617
- 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: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.2358 | 1.0 | 1635 | 0.1719 | 0.1758 | 0.1033 | 0.1554 | 0.1554 | 19.0 |
| 0.2043 | 2.0 | 3270 | 0.1574 | 0.1764 | 0.1046 | 0.1561 | 0.1561 | 19.0 |
| 0.191 | 3.0 | 4905 | 0.1505 | 0.1778 | 0.1069 | 0.1577 | 0.1578 | 19.0 |
| 0.178 | 4.0 | 6540 | 0.1448 | 0.1797 | 0.1093 | 0.1597 | 0.1597 | 19.0 |
| 0.1734 | 5.0 | 8175 | 0.1406 | 0.1804 | 0.1102 | 0.1605 | 0.1604 | 19.0 |
| 0.1681 | 6.0 | 9810 | 0.1376 | 0.1811 | 0.111 | 0.1613 | 0.1613 | 19.0 |
| 0.1665 | 7.0 | 11445 | 0.1365 | 0.1815 | 0.1114 | 0.1618 | 0.1618 | 19.0 |
| 0.1643 | 8.0 | 13080 | 0.1359 | 0.1813 | 0.1114 | 0.1616 | 0.1617 | 19.0 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
