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MarPla/LifeSciencePegasusLargeModel

sourceHugging Faceupdated 2y agoView on Hugging Face
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LifeSciencePegasusLargeModel

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: 5.6523
  • —Rouge1: 44.7761
  • —Rouge2: 12.6726
  • —Rougel: 29.0847
  • —Rougelsum: 40.7566
  • —Bertscore Precision: 77.9283
  • —Bertscore Recall: 81.5854
  • —Bertscore F1: 79.7092
  • —Bleu: 0.0886
  • —Gen Len: 225.7220

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
  • —trainbatchsize: 1
  • —evalbatchsize: 1
  • —seed: 42
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 16
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —num_epochs: 1

Training results

Training LossEpochStepValidation LossRouge1Rouge2RougelRougelsumBertscore PrecisionBertscore RecallBertscore F1BleuGen Len
6.25860.26433006.045340.194711.108226.971436.274776.634480.838578.67310.0775225.7220
6.02130.52866005.789943.244512.172228.456439.152477.519481.375579.39450.0856225.7220
5.90180.79299005.652344.776112.672629.084740.756677.928381.585479.70920.0886225.7220

Framework versions

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