T5_small_eurlexsum
This model is a fine-tuned version of t5-small on the eur-lex-sum dataset. It achieves the following results on the evaluation set:
- Loss: 0.9360
- Rouge1: 0.2288
- Rouge2: 0.1816
- Rougel: 0.2157
- Rougelsum: 0.2158
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 1.4482 | 0.1743 | 0.0982 | 0.1509 | 0.1511 | 19.0 |
| No log | 2.0 | 142 | 1.1661 | 0.193 | 0.1257 | 0.1731 | 0.1734 | 19.0 |
| No log | 3.0 | 213 | 1.0651 | 0.2072 | 0.1483 | 0.1892 | 0.1896 | 19.0 |
| No log | 4.0 | 284 | 1.0053 | 0.2167 | 0.1638 | 0.2017 | 0.2019 | 19.0 |
| No log | 5.0 | 355 | 0.9706 | 0.222 | 0.1731 | 0.2082 | 0.2079 | 19.0 |
| No log | 6.0 | 426 | 0.9510 | 0.2253 | 0.1771 | 0.2114 | 0.2114 | 19.0 |
| No log | 7.0 | 497 | 0.9393 | 0.2263 | 0.1785 | 0.2134 | 0.2133 | 19.0 |
| 1.4549 | 8.0 | 568 | 0.9360 | 0.2288 | 0.1816 | 0.2157 | 0.2158 | 19.0 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3