bart-base-asqa-cb
This model is a fine-tuned version of facebook/bart-base on the ASQA dataset. It achieves the following results on the evaluation set:
- Loss: 2.7878
- Rougelsum: 36.5701
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: 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rougelsum |
|---|---|---|---|---|
| No log | 1.0 | 273 | 2.9082 | 35.2452 |
| 3.4369 | 2.0 | 546 | 2.8642 | 35.9217 |
| 3.4369 | 3.0 | 819 | 2.8426 | 35.9304 |
| 3.1616 | 4.0 | 1092 | 2.8310 | 36.2562 |
| 3.1616 | 5.0 | 1365 | 2.8193 | 36.4633 |
| 3.0814 | 6.0 | 1638 | 2.8091 | 36.6044 |
| 3.0814 | 7.0 | 1911 | 2.8069 | 36.6191 |
| 3.0165 | 8.0 | 2184 | 2.8026 | 36.6380 |
| 3.0165 | 9.0 | 2457 | 2.7978 | 36.6962 |
| 2.9724 | 10.0 | 2730 | 2.7965 | 36.5703 |
| 2.9282 | 11.0 | 3003 | 2.7926 | 36.5339 |
| 2.9282 | 12.0 | 3276 | 2.7916 | 36.5093 |
| 2.8996 | 13.0 | 3549 | 2.7911 | 36.4693 |
| 2.8996 | 14.0 | 3822 | 2.7904 | 36.3852 |
| 2.8803 | 15.0 | 4095 | 2.7888 | 36.6173 |
| 2.8803 | 16.0 | 4368 | 2.7881 | 36.5282 |
| 2.8653 | 17.0 | 4641 | 2.7885 | 36.6131 |
| 2.8653 | 18.0 | 4914 | 2.7878 | 36.6120 |
| 2.8558 | 19.0 | 5187 | 2.7877 | 36.5637 |
| 2.8558 | 20.0 | 5460 | 2.7878 | 36.5701 |
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1