t5-base-pt-asqa-ob
This model is a fine-tuned version of din0s/t5-base-msmarco-nlgen-ob on the ASQA dataset. It achieves the following results on the evaluation set:
- Loss: 1.7481
- Rougelsum: 12.3722
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rougelsum |
|---|---|---|---|---|
| No log | 1.0 | 355 | 1.8760 | 11.5138 |
| 2.1344 | 2.0 | 710 | 1.8322 | 11.6843 |
| 1.979 | 3.0 | 1065 | 1.8109 | 11.8592 |
| 1.979 | 4.0 | 1420 | 1.7967 | 11.9466 |
| 1.9493 | 5.0 | 1775 | 1.7871 | 12.0333 |
| 1.9099 | 6.0 | 2130 | 1.7778 | 12.0805 |
| 1.9099 | 7.0 | 2485 | 1.7720 | 12.1659 |
| 1.8748 | 8.0 | 2840 | 1.7668 | 12.2039 |
| 1.8584 | 9.0 | 3195 | 1.7628 | 12.2506 |
| 1.8362 | 10.0 | 3550 | 1.7601 | 12.2557 |
| 1.8362 | 11.0 | 3905 | 1.7575 | 12.2718 |
| 1.8134 | 12.0 | 4260 | 1.7562 | 12.2789 |
| 1.7996 | 13.0 | 4615 | 1.7538 | 12.3179 |
| 1.7996 | 14.0 | 4970 | 1.7529 | 12.3035 |
| 1.8049 | 15.0 | 5325 | 1.7519 | 12.3317 |
| 1.7898 | 16.0 | 5680 | 1.7510 | 12.3717 |
| 1.7872 | 17.0 | 6035 | 1.7497 | 12.3750 |
| 1.7872 | 18.0 | 6390 | 1.7486 | 12.3580 |
| 1.7759 | 19.0 | 6745 | 1.7483 | 12.3698 |
| 1.785 | 20.0 | 7100 | 1.7481 | 12.3722 |
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1