bart-pt-asqa-ob
This model is a fine-tuned version of vblagoje/bart_lfqa on the ASQA dataset. It achieves the following results on the evaluation set:
- Loss: 1.6901
- Rougelsum: 20.7527
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 | 1.6295 | 17.7502 |
| 1.6407 | 2.0 | 710 | 1.6144 | 18.5897 |
| 1.4645 | 3.0 | 1065 | 1.6222 | 19.3778 |
| 1.4645 | 4.0 | 1420 | 1.6522 | 19.6941 |
| 1.3678 | 5.0 | 1775 | 1.6528 | 20.3110 |
| 1.2671 | 6.0 | 2130 | 1.6879 | 20.6112 |
| 1.2671 | 7.0 | 2485 | 1.6901 | 20.7527 |
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
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