readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - null
  metrics:
  - rouge
  model_index:
  - name: bart-base-finetuned-xsum
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      metric:
        name: Rouge1
        type: rouge
        value: 27.887
  ---
  
  <!-- 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-base-finetuned-xsum
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5925
  - Rouge1: 27.887
  - Rouge2: 16.1414
  - Rougel: 24.0525
  - Rougelsum: 25.4029
  - Gen Len: 19.9841
  
  ## 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
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:---------:|:-------:|
  | 1.9826        | 1.0   | 879  | 1.5925          | 27.887 | 16.1414 | 24.0525 | 25.4029   | 19.9841 |
  
  
  ### Framework versions
  
  - Transformers 4.9.2
  - Pytorch 1.9.0+cu102
  - Datasets 1.11.0
  - Tokenizers 0.10.3
  