readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-large-cnn-finetuned-xsum
    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. -->
  
  # bart-large-cnn-finetuned-xsum
  
  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.7973
  - Rouge1: 24.5661
  - Rouge2: 8.6188
  - Rougel: 17.1387
  - Rougelsum: 18.869
  - Gen Len: 73.1667
  
  ## 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-08
  - train_batch_size: 3
  - eval_batch_size: 3
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 24   | 3.7983          | 24.5842 | 8.6062 | 17.0846 | 18.8412   | 73.3472 |
  | No log        | 2.0   | 48   | 3.7973          | 24.5661 | 8.6188 | 17.1387 | 18.869    | 73.1667 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  