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metadata
license: apache-2.0
tags:
  - summarisation
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: distilbart-xsum-6-6-finetuned-bbc-news-on-abstractive
    results: []

distilbart-xsum-6-6-finetuned-bbc-news-on-abstractive

This model is a fine-tuned version of sshleifer/distilbart-xsum-6-6 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6549
  • Rouge1: 38.9186
  • Rouge2: 30.2223
  • Rougel: 32.6201
  • Rougelsum: 37.7502

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.3838 1.0 445 1.4841 39.1621 30.4379 32.6613 37.9963
1.0077 2.0 890 1.5173 39.388 30.9125 33.099 38.2442
0.7983 3.0 1335 1.5726 38.7913 30.0766 32.6092 37.5953
0.6681 4.0 1780 1.6549 38.9186 30.2223 32.6201 37.7502

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1