bart-base-finetuned-xsum

This model is a fine-tuned version of facebook/bart-base on the xsum dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1755
  • Rouge1: 34.6293
  • Rouge2: 13.4749
  • Rougel: 28.2616
  • Rougelsum: 28.2553

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: 10
  • eval_batch_size: 10
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.4765 1.0 1000 2.0873 33.9596 12.722 27.4135 27.4062
1.9854 2.0 2000 2.0802 33.6802 12.8965 27.4061 27.4064
1.6677 3.0 3000 2.0998 34.2038 13.1362 27.8808 27.8806
1.4313 4.0 4000 2.1404 34.8491 13.4154 28.2768 28.2702
1.275 5.0 5000 2.1755 34.6293 13.4749 28.2616 28.2553

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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Dataset used to train Hemantjangra/bart-base-finetuned-xsum

Evaluation results