readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-12-6-sec
    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-cnn-12-6-sec
  
  This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0798
  - Rouge1: 72.1665
  - Rouge2: 62.2601
  - Rougel: 67.8376
  - Rougelsum: 71.1407
  - Gen Len: 121.62
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 99   | 0.3526          | 53.3978 | 38.6395 | 45.6271 | 51.0477   | 111.48  |
  | No log        | 2.0   | 198  | 0.1961          | 55.7397 | 43.6293 | 50.9595 | 54.0764   | 111.46  |
  | No log        | 3.0   | 297  | 0.1483          | 66.9443 | 54.8966 | 62.6678 | 65.6787   | 118.64  |
  | No log        | 4.0   | 396  | 0.1218          | 67.2661 | 56.1852 | 63.1339 | 65.8066   | 124.92  |
  | No log        | 5.0   | 495  | 0.1139          | 67.2097 | 55.8694 | 62.7508 | 65.9706   | 123.02  |
  | 0.4156        | 6.0   | 594  | 0.0940          | 71.607  | 60.6697 | 66.7873 | 70.339    | 122.84  |
  | 0.4156        | 7.0   | 693  | 0.0888          | 71.3792 | 61.8326 | 68.25   | 70.5113   | 124.4   |
  | 0.4156        | 8.0   | 792  | 0.0870          | 72.7472 | 62.6968 | 68.2853 | 71.5789   | 124.34  |
  | 0.4156        | 9.0   | 891  | 0.0799          | 73.4438 | 63.5966 | 68.8737 | 72.3014   | 119.88  |
  | 0.4156        | 10.0  | 990  | 0.0798          | 72.1665 | 62.2601 | 67.8376 | 71.1407   | 121.62  |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  