readme: ---
  license: apache-2.0
  tags:
  - summarisation
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-xsum-6-6-finetuned-bbc-news-on-abstractive
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # distilbart-xsum-6-6-finetuned-bbc-news-on-abstractive
  
  This model is a fine-tuned version of [sshleifer/distilbart-xsum-6-6](https://huggingface.co/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
  