readme: ---
  license: apache-2.0
  tags:
  - summarisation
  - generated_from_trainer
  datasets:
  - multi_news
  metrics:
  - rouge
  model-index:
  - name: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi-news
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: multi_news
        type: multi_news
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 38.9616
  ---
  
  <!-- 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. -->
  
  # bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi-news
  
  This model is a fine-tuned version of [mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization) on the multi_news dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.0185
  - Rouge1: 38.9616
  - Rouge2: 14.1539
  - Rougel: 21.1788
  - Rougelsum: 35.314
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 3.3679        | 1.0   | 11243 | 3.1314          | 38.4459 | 13.7777 | 20.8772 | 34.8321   |
  | 3.1115        | 2.0   | 22486 | 3.0589          | 38.7419 | 13.9355 | 20.9911 | 35.0988   |
  | 2.9826        | 3.0   | 33729 | 3.0311          | 38.7345 | 14.0365 | 21.0571 | 35.1604   |
  | 2.8986        | 4.0   | 44972 | 3.0185          | 38.9616 | 14.1539 | 21.1788 | 35.314    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  