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

  • Loss: 4.1359
  • Rouge1: 0.3914
  • Rouge2: 0.1399
  • Rougel: 0.2039
  • Rougelsum: 0.3504
  • Gen Len: 141.64

Model description

This model was created to generate summaries of news articles.

Intended uses & limitations

The model takes up to maximum article length of 1024 tokens and generates a summary of maximum length of 512 tokens.

Training and evaluation data

This model was trained on 1000 articles and summaries from the Multi-News dataset. https://arxiv.org/abs/1906.01749

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10
  • label_smoothing_factor: 0.1

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Dataset used to train debbiesoon/bart_large_summarise_v3

Evaluation results