NLP-Paper-to-QA-Generation
This model is a fine-tuned version of google/pegasus-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9593
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 184
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.99 | 46 | 4.8204 |
| 5.3975 | 1.99 | 92 | 4.4450 |
| 5.3975 | 2.98 | 138 | 3.9634 |
| 4.494 | 3.97 | 184 | 3.4658 |
| 4.494 | 4.97 | 230 | 3.1863 |
| 3.5664 | 5.96 | 276 | 3.0828 |
| 3.5664 | 6.95 | 322 | 3.0403 |
| 3.2954 | 7.95 | 368 | 3.0155 |
| 3.2954 | 8.94 | 414 | 2.9989 |
| 3.1918 | 9.93 | 460 | 2.9826 |
| 3.1918 | 10.93 | 506 | 2.9742 |
| 3.1547 | 11.92 | 552 | 2.9670 |
| 3.1547 | 12.91 | 598 | 2.9620 |
| 3.1233 | 13.91 | 644 | 2.9601 |
| 3.1233 | 14.9 | 690 | 2.9593 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for UNIST-Eunchan/NLP-Paper-to-QA-Generation
Base model
google/pegasus-large