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sumarize_model_pegasus_v1

This model is a fine-tuned version of google/pegasus-xsum on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3379
  • Rouge1: 0.6034
  • Rouge2: 0.4459
  • Rougel: 0.5685
  • Rougelsum: 0.5681
  • Gen Len: 32.8647

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: 3.419313942464226e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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 Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 239 1.4418 0.6747 0.5033 0.6338 0.6335 43.9549
No log 2.0 478 1.3434 0.6869 0.5148 0.646 0.6459 44.938
1.8531 3.0 717 1.2791 0.6843 0.5141 0.6451 0.645 44.7556
1.8531 4.0 956 1.2358 0.6868 0.5168 0.6473 0.647 44.4305
1.4419 5.0 1195 1.2654 0.6858 0.5172 0.6467 0.6464 43.7857
1.4419 6.0 1434 1.2838 0.6686 0.4999 0.6291 0.6288 39.9549
1.4368 7.0 1673 1.3379 0.6034 0.4459 0.5685 0.5681 32.8647

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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