bart-base-asqa-ob
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8291
- Rougelsum: 13.0645
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: 5e-06
- 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 | 1.9076 | 13.1069 |
| 2.2336 | 2.0 | 710 | 1.8749 | 13.0551 |
| 2.048 | 3.0 | 1065 | 1.8580 | 13.1287 |
| 2.048 | 4.0 | 1420 | 1.8413 | 13.1473 |
| 2.0003 | 5.0 | 1775 | 1.8451 | 13.1264 |
| 1.9423 | 6.0 | 2130 | 1.8360 | 13.0959 |
| 1.9423 | 7.0 | 2485 | 1.8372 | 13.1289 |
| 1.8894 | 8.0 | 2840 | 1.8275 | 13.1359 |
| 1.8568 | 9.0 | 3195 | 1.8241 | 13.0983 |
| 1.8279 | 10.0 | 3550 | 1.8279 | 13.0184 |
| 1.8279 | 11.0 | 3905 | 1.8275 | 13.1177 |
| 1.7871 | 12.0 | 4260 | 1.8279 | 13.0871 |
| 1.7666 | 13.0 | 4615 | 1.8295 | 13.0992 |
| 1.7666 | 14.0 | 4970 | 1.8291 | 13.0645 |
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1