readme: ---
  license: apache-2.0
  tags:
  - summarization
  datasets:
  - multi_news
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-12-6-ftn-multi_news
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: summarization
      dataset:
        name: multi_news
        type: multi_news
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 41.6136
    - task:
        type: summarization
        name: Summarization
      dataset:
        name: multi_news
        type: multi_news
        config: default
        split: test
      metrics:
      - name: ROUGE-1
        type: rouge
        value: 39.6512
        verified: true
      - name: ROUGE-2
        type: rouge
        value: 14.333
        verified: true
      - name: ROUGE-L
        type: rouge
        value: 21.5797
        verified: true
      - name: ROUGE-LSUM
        type: rouge
        value: 35.5793
        verified: true
      - name: loss
        type: loss
        value: 5.507579803466797
        verified: true
      - name: gen_len
        type: gen_len
        value: 132.1745
        verified: true
  ---
  
  <!-- 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-cnn-12-6-ftn-multi_news
  
  This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the multi_news dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.8143
  - Rouge1: 41.6136
  - Rouge2: 14.7454
  - Rougel: 23.3597
  - Rougelsum: 36.1973
  - Gen Len: 130.874
  
  ## 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: 4
  - eval_batch_size: 4
  - 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: 1
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 3.8821        | 0.89  | 2000 | 3.8143          | 41.6136 | 14.7454 | 23.3597 | 36.1973   | 130.874 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  