readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - xsum
  metrics:
  - rouge
  model-index:
  - name: bart-base-facebook
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: xsum
        type: xsum
        config: default
        split: train
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 0.7146
  ---
  
  <!-- 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-facebook
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the xsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.1877
  - Rouge1: 0.7146
  - Rouge2: 0.3305
  - Rougel: 0.2988
  - Rougelsum: 0.6822
  
  ## 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: 10
  - eval_batch_size: 10
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 2.505         | 1.0   | 1359 | 2.1048          | 0.6788 | 0.3022 | 0.2843 | 0.6497    |
  | 2.0216        | 2.0   | 2718 | 2.1010          | 0.7022 | 0.3182 | 0.2974 | 0.672     |
  | 1.7088        | 3.0   | 4077 | 2.1228          | 0.7048 | 0.3214 | 0.2968 | 0.6722    |
  | 1.4778        | 4.0   | 5436 | 2.1655          | 0.7117 | 0.325  | 0.2984 | 0.6786    |
  | 1.3161        | 5.0   | 6795 | 2.1877          | 0.7146 | 0.3305 | 0.2988 | 0.6822    |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  