readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-base-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-base-finetuned-xsum
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5585
  - Rouge1: 0.8859
  - Rouge2: 0.8467
  - Rougel: 0.8883
  - Rougelsum: 0.8879
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | No log        | 1.0   | 41   | 0.4596          | 0.8845 | 0.849  | 0.8874 | 0.8865    |
  | No log        | 2.0   | 82   | 0.4047          | 0.8839 | 0.8466 | 0.8852 | 0.8836    |
  | No log        | 3.0   | 123  | 0.4587          | 0.8765 | 0.836  | 0.8783 | 0.8755    |
  | No log        | 4.0   | 164  | 0.4488          | 0.8785 | 0.8389 | 0.8811 | 0.8784    |
  | No log        | 5.0   | 205  | 0.4443          | 0.8564 | 0.8084 | 0.855  | 0.8543    |
  | No log        | 6.0   | 246  | 0.4643          | 0.8965 | 0.8614 | 0.8981 | 0.8965    |
  | No log        | 7.0   | 287  | 0.4782          | 0.8831 | 0.8468 | 0.885  | 0.8836    |
  | No log        | 8.0   | 328  | 0.4870          | 0.853  | 0.8051 | 0.8554 | 0.8541    |
  | No log        | 9.0   | 369  | 0.4766          | 0.9029 | 0.8659 | 0.9052 | 0.9027    |
  | No log        | 10.0  | 410  | 0.5023          | 0.8924 | 0.8528 | 0.895  | 0.8926    |
  | No log        | 11.0  | 451  | 0.5254          | 0.8689 | 0.8234 | 0.8699 | 0.8692    |
  | No log        | 12.0  | 492  | 0.4996          | 0.8833 | 0.8424 | 0.8851 | 0.8843    |
  | 0.1489        | 13.0  | 533  | 0.5095          | 0.8747 | 0.8345 | 0.8762 | 0.8749    |
  | 0.1489        | 14.0  | 574  | 0.5034          | 0.868  | 0.8226 | 0.8699 | 0.8689    |
  | 0.1489        | 15.0  | 615  | 0.4976          | 0.8609 | 0.8112 | 0.8632 | 0.8617    |
  | 0.1489        | 16.0  | 656  | 0.5122          | 0.9055 | 0.8722 | 0.9068 | 0.9069    |
  | 0.1489        | 17.0  | 697  | 0.5204          | 0.845  | 0.7954 | 0.8482 | 0.8461    |
  | 0.1489        | 18.0  | 738  | 0.5363          | 0.8911 | 0.8528 | 0.8934 | 0.8919    |
  | 0.1489        | 19.0  | 779  | 0.5572          | 0.8943 | 0.8594 | 0.8963 | 0.8956    |
  | 0.1489        | 20.0  | 820  | 0.5469          | 0.9031 | 0.8688 | 0.9047 | 0.9047    |
  | 0.1489        | 21.0  | 861  | 0.5508          | 0.8848 | 0.8472 | 0.887  | 0.8869    |
  | 0.1489        | 22.0  | 902  | 0.5579          | 0.8724 | 0.8306 | 0.8747 | 0.8737    |
  | 0.1489        | 23.0  | 943  | 0.5508          | 0.8772 | 0.8397 | 0.8808 | 0.8803    |
  | 0.1489        | 24.0  | 984  | 0.5658          | 0.8627 | 0.8153 | 0.8645 | 0.8637    |
  | 0.0336        | 25.0  | 1025 | 0.5539          | 0.904  | 0.8702 | 0.9052 | 0.9058    |
  | 0.0336        | 26.0  | 1066 | 0.5605          | 0.9004 | 0.8659 | 0.9026 | 0.9017    |
  | 0.0336        | 27.0  | 1107 | 0.5589          | 0.899  | 0.8644 | 0.9012 | 0.9005    |
  | 0.0336        | 28.0  | 1148 | 0.5558          | 0.8872 | 0.8488 | 0.8894 | 0.889     |
  | 0.0336        | 29.0  | 1189 | 0.5570          | 0.8859 | 0.8467 | 0.8883 | 0.8879    |
  | 0.0336        | 30.0  | 1230 | 0.5585          | 0.8859 | 0.8467 | 0.8883 | 0.8879    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  