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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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