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t5-small-finetune-xsum
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4414
- Rouge1: 29.3266
- Rouge2: 8.4122
- Rougel: 23.086
- Rougelsum: 23.0988
- Gen Len: 18.8112
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7808 | 1.0 | 2000 | 2.5082 | 27.7519 | 7.446 | 21.7066 | 21.7226 | 18.835 |
| 2.748 | 2.0 | 4000 | 2.4904 | 27.9132 | 7.5749 | 21.9684 | 21.9859 | 18.81 |
| 2.6996 | 3.0 | 6000 | 2.4786 | 28.2767 | 7.8416 | 22.1965 | 22.2152 | 18.785 |
| 2.6992 | 4.0 | 8000 | 2.4694 | 28.6795 | 7.9755 | 22.4116 | 22.437 | 18.8275 |
| 2.6118 | 5.0 | 10000 | 2.4627 | 28.6839 | 7.9493 | 22.4375 | 22.4522 | 18.8075 |
| 2.6242 | 6.0 | 12000 | 2.4549 | 28.8803 | 8.1118 | 22.6837 | 22.6895 | 18.8169 |
| 2.5889 | 7.0 | 14000 | 2.4523 | 29.0163 | 8.2553 | 22.9279 | 22.9428 | 18.8281 |
| 2.5689 | 8.0 | 16000 | 2.4515 | 28.9347 | 8.1521 | 22.7739 | 22.7803 | 18.8169 |
| 2.5309 | 9.0 | 18000 | 2.4490 | 29.1943 | 8.2996 | 23.0166 | 23.005 | 18.8238 |
| 2.5179 | 10.0 | 20000 | 2.4460 | 29.1816 | 8.3726 | 23.0678 | 23.0622 | 18.8025 |
| 2.5114 | 11.0 | 22000 | 2.4451 | 29.1586 | 8.3156 | 23.0407 | 23.0485 | 18.8094 |
| 2.4775 | 12.0 | 24000 | 2.4440 | 29.2132 | 8.452 | 23.0056 | 23.0021 | 18.8069 |
| 2.5082 | 13.0 | 26000 | 2.4440 | 29.1495 | 8.3541 | 22.9148 | 22.9349 | 18.8025 |
| 2.4888 | 14.0 | 28000 | 2.4431 | 29.2776 | 8.3071 | 23.0654 | 23.0685 | 18.8138 |
| 2.479 | 15.0 | 30000 | 2.4431 | 29.378 | 8.4205 | 23.1346 | 23.1347 | 18.8044 |
| 2.4464 | 16.0 | 32000 | 2.4427 | 29.3569 | 8.4209 | 23.0688 | 23.0814 | 18.8038 |
| 2.4431 | 17.0 | 34000 | 2.4423 | 29.2736 | 8.3856 | 23.0737 | 23.0696 | 18.8188 |
| 2.447 | 18.0 | 36000 | 2.4419 | 29.2725 | 8.41 | 23.0817 | 23.1089 | 18.8125 |
| 2.4626 | 19.0 | 38000 | 2.4416 | 29.3144 | 8.3858 | 23.0861 | 23.0993 | 18.8075 |
| 2.4362 | 20.0 | 40000 | 2.4414 | 29.3266 | 8.4122 | 23.086 | 23.0988 | 18.8112 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
