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LifeMainSectionsPegasusLargeModel

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: 5.8222
  • Rouge1: 42.8874
  • Rouge2: 11.2364
  • Rougel: 27.5064
  • Rougelsum: 39.4117
  • Bertscore Precision: 77.6554
  • Bertscore Recall: 81.0536
  • Bertscore F1: 79.3129
  • Bleu: 0.0730
  • Gen Len: 227.0514

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-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: 500
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Bertscore Precision Bertscore Recall Bertscore F1 Bleu Gen Len
6.9298 0.0888 100 6.6509 32.8681 7.0176 21.3819 29.8291 74.6005 79.1172 76.7856 0.0454 227.0514
6.6156 0.1776 200 6.3485 36.1792 8.8919 24.1486 33.0206 75.7824 79.9379 77.7981 0.0585 227.0514
6.4148 0.2664 300 6.2282 39.2098 10.0222 25.6326 35.6 76.2724 80.3779 78.2642 0.0655 227.0514
6.3735 0.3552 400 6.1269 39.6145 10.3955 25.9037 36.142 76.2138 80.4372 78.2611 0.0675 227.0514
6.2031 0.4440 500 6.0437 40.2044 10.3808 26.2646 36.6302 76.3888 80.5312 78.3982 0.0674 227.0514
6.1976 0.5328 600 5.9679 41.4546 10.6953 26.6781 37.9643 76.9224 80.7265 78.7724 0.0695 227.0514
6.1576 0.6216 700 5.9134 41.8873 10.8176 26.9451 38.6303 77.3503 80.8194 79.0412 0.0704 227.0514
6.123 0.7104 800 5.8734 41.4092 10.7374 26.9369 37.8851 77.0833 80.8538 78.9178 0.0699 227.0514
6.0612 0.7992 900 5.8530 43.3281 11.3695 27.52 39.7303 77.5853 81.0567 79.2776 0.0736 227.0514
6.0503 0.8880 1000 5.8316 42.7407 11.1329 27.4419 39.2638 77.6592 81.0404 79.3085 0.0724 227.0514
6.1028 0.9767 1100 5.8222 42.8874 11.2364 27.5064 39.4117 77.6554 81.0536 79.3129 0.0730 227.0514

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.2.1
  • Tokenizers 0.19.1
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