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distilbart-xsum-12-1-finetuned-pubmed

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-1 on the pub_med_summarization_dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 2.8236
  • Rouge1: 27.0012
  • Rouge2: 12.728
  • Rougel: 19.8685
  • Rougelsum: 25.0485
  • Gen Len: 59.969

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: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.3604 1.0 4000 3.1575 25.0078 11.5381 18.4246 23.1605 54.8935
3.0697 2.0 8000 2.9478 26.4947 12.5411 19.4328 24.6123 57.948
2.8638 3.0 12000 2.8672 26.8856 12.7568 19.8949 24.8745 59.6245
2.7243 4.0 16000 2.8347 26.7347 12.5152 19.6516 24.7756 60.439
2.6072 5.0 20000 2.8236 27.0012 12.728 19.8685 25.0485 59.969

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.3
  • Tokenizers 0.11.6
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Evaluation results