t5-base-asqa-ob
This model is a fine-tuned version of t5-base on the ASQA dataset. It achieves the following results on the evaluation set:
- Loss: 1.7356
- Rougelsum: 12.0879
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 | 1.8545 | 11.6549 |
| 2.4887 | 2.0 | 710 | 1.8050 | 11.7533 |
| 1.9581 | 3.0 | 1065 | 1.7843 | 11.8327 |
| 1.9581 | 4.0 | 1420 | 1.7722 | 11.9442 |
| 1.9252 | 5.0 | 1775 | 1.7648 | 11.9331 |
| 1.8853 | 6.0 | 2130 | 1.7567 | 11.9788 |
| 1.8853 | 7.0 | 2485 | 1.7519 | 12.0300 |
| 1.8512 | 8.0 | 2840 | 1.7483 | 12.0225 |
| 1.8328 | 9.0 | 3195 | 1.7451 | 12.0402 |
| 1.8115 | 10.0 | 3550 | 1.7436 | 12.0444 |
| 1.8115 | 11.0 | 3905 | 1.7419 | 12.0850 |
| 1.7878 | 12.0 | 4260 | 1.7408 | 12.1047 |
| 1.774 | 13.0 | 4615 | 1.7394 | 12.0839 |
| 1.774 | 14.0 | 4970 | 1.7390 | 12.0910 |
| 1.7787 | 15.0 | 5325 | 1.7381 | 12.0880 |
| 1.7632 | 16.0 | 5680 | 1.7380 | 12.1088 |
| 1.7623 | 17.0 | 6035 | 1.7370 | 12.1046 |
| 1.7623 | 18.0 | 6390 | 1.7368 | 12.0997 |
| 1.7508 | 19.0 | 6745 | 1.7359 | 12.0902 |
| 1.7597 | 20.0 | 7100 | 1.7356 | 12.0879 |
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
- Downloads last month
- 5
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support