<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
t5-small-finetune-cnn
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9579
- Rouge1: 24.7426
- Rouge2: 10.4667
- Rougel: 20.2334
- Rougelsum: 23.0122
- 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: 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 |
|---|---|---|---|---|---|---|---|---|
| 1.9721 | 1.0 | 2000 | 1.9608 | 25.1804 | 10.8327 | 20.5778 | 23.3974 | 19.0 |
| 1.9466 | 2.0 | 4000 | 1.9549 | 25.0152 | 10.6784 | 20.4465 | 23.2601 | 19.0 |
| 1.8932 | 3.0 | 6000 | 1.9515 | 25.0464 | 10.7024 | 20.3992 | 23.2249 | 19.0 |
| 1.8564 | 4.0 | 8000 | 1.9489 | 25.0313 | 10.642 | 20.3601 | 23.2032 | 19.0 |
| 1.862 | 5.0 | 10000 | 1.9510 | 24.9582 | 10.614 | 20.3625 | 23.1762 | 19.0 |
| 1.8478 | 6.0 | 12000 | 1.9502 | 25.032 | 10.7084 | 20.4506 | 23.2435 | 19.0 |
| 1.819 | 7.0 | 14000 | 1.9495 | 24.7874 | 10.4848 | 20.2893 | 23.0832 | 19.0 |
| 1.7869 | 8.0 | 16000 | 1.9470 | 24.7095 | 10.4465 | 20.1705 | 22.9248 | 19.0 |
| 1.8068 | 9.0 | 18000 | 1.9510 | 24.705 | 10.4407 | 20.1684 | 22.9817 | 19.0 |
| 1.768 | 10.0 | 20000 | 1.9517 | 24.6067 | 10.4281 | 20.0765 | 22.9034 | 19.0 |
| 1.7713 | 11.0 | 22000 | 1.9524 | 24.6871 | 10.4126 | 20.1802 | 22.962 | 19.0 |
| 1.7635 | 12.0 | 24000 | 1.9548 | 24.5998 | 10.3969 | 20.1427 | 22.9191 | 19.0 |
| 1.7625 | 13.0 | 26000 | 1.9561 | 24.66 | 10.4032 | 20.1732 | 22.9256 | 19.0 |
| 1.7461 | 14.0 | 28000 | 1.9551 | 24.7071 | 10.4209 | 20.1833 | 22.9803 | 19.0 |
| 1.7271 | 15.0 | 30000 | 1.9558 | 24.6682 | 10.4162 | 20.198 | 22.9445 | 19.0 |
| 1.7452 | 16.0 | 32000 | 1.9563 | 24.8148 | 10.4558 | 20.2123 | 23.0374 | 19.0 |
| 1.7489 | 17.0 | 34000 | 1.9576 | 24.6459 | 10.3782 | 20.1213 | 22.8918 | 19.0 |
| 1.724 | 18.0 | 36000 | 1.9581 | 24.7384 | 10.427 | 20.2088 | 22.9971 | 19.0 |
| 1.7236 | 19.0 | 38000 | 1.9581 | 24.7366 | 10.4394 | 20.2028 | 23.0286 | 19.0 |
| 1.7331 | 20.0 | 40000 | 1.9579 | 24.7426 | 10.4667 | 20.2334 | 23.0122 | 19.0 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
