pegasus-xsum-clara-med

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: 1.9013
  • Rouge1: 43.7595
  • Rouge2: 25.7022
  • Rougel: 39.6153
  • Rougelsum: 39.7151

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: 5.6e-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: 30

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
No log 1.0 190 2.5468 41.6125 24.1264 37.7704 37.8615
No log 2.0 380 2.3603 41.9598 24.315 38.1087 38.217
2.7787 3.0 570 2.2604 42.0463 24.5067 38.1632 38.2716
2.7787 4.0 760 2.1846 42.1471 24.639 38.3677 38.471
2.2691 5.0 950 2.1361 42.4562 24.8962 38.6107 38.7065
2.2691 6.0 1140 2.0887 42.6005 24.947 38.7049 38.805
2.2691 7.0 1330 2.0617 42.7946 24.9509 38.9123 39.0003
2.0313 8.0 1520 2.0222 43.0201 25.3552 39.151 39.266
2.0313 9.0 1710 2.0049 43.2293 25.4719 39.4239 39.4944
1.872 10.0 1900 1.9899 43.2629 25.5285 39.4124 39.4591
1.872 11.0 2090 1.9772 43.4294 25.8006 39.5863 39.6726
1.872 12.0 2280 1.9630 43.63 25.7259 39.5521 39.6888
1.7497 13.0 2470 1.9513 43.4053 25.5567 39.4567 39.5918
1.7497 14.0 2660 1.9336 43.2584 25.4554 39.2917 39.3944
1.6609 15.0 2850 1.9345 43.2644 25.5958 39.3474 39.4645
1.6609 16.0 3040 1.9152 43.4404 25.6127 39.4472 39.5418
1.6609 17.0 3230 1.9106 43.2751 25.3213 39.2723 39.3871
1.5809 18.0 3420 1.9125 43.2335 25.341 39.2705 39.3577
1.5809 19.0 3610 1.9086 43.1679 25.3275 39.1858 39.303
1.5221 20.0 3800 1.9030 43.2794 25.4126 39.2902 39.4092
1.5221 21.0 3990 1.8996 43.1731 25.3819 39.1873 39.3172
1.5221 22.0 4180 1.9006 43.4949 25.4485 39.3092 39.4516
1.4714 23.0 4370 1.8977 43.5657 25.5974 39.4489 39.5257
1.4714 24.0 4560 1.9035 43.6444 25.6794 39.5809 39.683
1.4421 25.0 4750 1.9000 43.4825 25.5898 39.4319 39.4973
1.4421 26.0 4940 1.9030 43.4623 25.5726 39.461 39.6009
1.4421 27.0 5130 1.8993 43.3357 25.5518 39.3897 39.4672
1.4139 28.0 5320 1.9009 43.5834 25.7211 39.584 39.6725
1.4139 29.0 5510 1.9002 43.7115 25.6997 39.6603 39.7621
1.4016 30.0 5700 1.9013 43.7595 25.7022 39.6153 39.7151

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0
  • Datasets 2.8.0
  • Tokenizers 0.12.1
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