t5-base-asqa-cb
This model is a fine-tuned version of t5-base on the ASQA dataset. It achieves the following results on the evaluation set:
- Loss: 2.7489
- Rougelsum: 26.6134
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Rougelsum |
|---|---|---|---|---|
| No log | 1.0 | 273 | 2.9648 | 23.8374 |
| 3.5538 | 2.0 | 546 | 2.9054 | 24.2701 |
| 3.5538 | 3.0 | 819 | 2.8744 | 24.4172 |
| 3.1468 | 4.0 | 1092 | 2.8557 | 24.5949 |
| 3.1468 | 5.0 | 1365 | 2.8400 | 24.7069 |
| 3.0711 | 6.0 | 1638 | 2.8280 | 24.8685 |
| 3.0711 | 7.0 | 1911 | 2.8191 | 24.9829 |
| 3.0348 | 8.0 | 2184 | 2.8109 | 25.0908 |
| 3.0348 | 9.0 | 2457 | 2.8038 | 25.2485 |
| 2.9962 | 10.0 | 2730 | 2.7978 | 25.3279 |
| 2.9635 | 11.0 | 3003 | 2.7920 | 25.4465 |
| 2.9635 | 12.0 | 3276 | 2.7878 | 25.5927 |
| 2.9328 | 13.0 | 3549 | 2.7833 | 25.6925 |
| 2.9328 | 14.0 | 3822 | 2.7809 | 25.7563 |
| 2.9126 | 15.0 | 4095 | 2.7773 | 25.8123 |
| 2.9126 | 16.0 | 4368 | 2.7747 | 25.9039 |
| 2.8878 | 17.0 | 4641 | 2.7719 | 25.9636 |
| 2.8878 | 18.0 | 4914 | 2.7693 | 26.0025 |
| 2.8744 | 19.0 | 5187 | 2.7673 | 26.0578 |
| 2.8744 | 20.0 | 5460 | 2.7656 | 26.1161 |
| 2.8579 | 21.0 | 5733 | 2.7629 | 26.1490 |
| 2.8418 | 22.0 | 6006 | 2.7614 | 26.1830 |
| 2.8418 | 23.0 | 6279 | 2.7604 | 26.2146 |
| 2.8256 | 24.0 | 6552 | 2.7586 | 26.2899 |
| 2.8256 | 25.0 | 6825 | 2.7586 | 26.2724 |
| 2.8093 | 26.0 | 7098 | 2.7566 | 26.3183 |
| 2.8093 | 27.0 | 7371 | 2.7551 | 26.3365 |
| 2.8083 | 28.0 | 7644 | 2.7546 | 26.3950 |
| 2.8083 | 29.0 | 7917 | 2.7537 | 26.4357 |
| 2.7917 | 30.0 | 8190 | 2.7529 | 26.4681 |
| 2.7917 | 31.0 | 8463 | 2.7526 | 26.5021 |
| 2.785 | 32.0 | 8736 | 2.7512 | 26.5241 |
| 2.7779 | 33.0 | 9009 | 2.7510 | 26.5361 |
| 2.7779 | 34.0 | 9282 | 2.7502 | 26.5620 |
| 2.771 | 35.0 | 9555 | 2.7495 | 26.6038 |
| 2.771 | 36.0 | 9828 | 2.7488 | 26.6161 |
| 2.7647 | 37.0 | 10101 | 2.7489 | 26.6134 |
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1