readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-base-finetuned-xlsum-with-multi-news-10-epoch
    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-xlsum-with-multi-news-10-epoch
  
  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: 1.7450
  - Rouge1: 38.4651
  - Rouge2: 17.181
  - Rougel: 31.5511
  - Rougelsum: 31.6061
  - Gen Len: 19.6752
  
  ## 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: 16
  - eval_batch_size: 16
  - 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 |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.2151        | 1.0   | 20543  | 1.8364          | 36.8242 | 15.4678 | 29.9179 | 29.9756   | 19.5911 |
  | 2.0765        | 2.0   | 41086  | 1.7958          | 37.2066 | 15.9599 | 30.3947 | 30.4615   | 19.5761 |
  | 1.9964        | 3.0   | 61629  | 1.7740          | 37.5972 | 16.3675 | 30.7002 | 30.7514   | 19.6134 |
  | 1.9353        | 4.0   | 82172  | 1.7585          | 37.9193 | 16.6538 | 31.0422 | 31.0914   | 19.5524 |
  | 1.8762        | 5.0   | 102715 | 1.7495          | 38.1038 | 16.8408 | 31.2435 | 31.2985   | 19.628  |
  | 1.8289        | 6.0   | 123258 | 1.7471          | 38.0699 | 16.8839 | 31.2437 | 31.2997   | 19.6085 |
  | 1.7968        | 7.0   | 143801 | 1.7422          | 38.2211 | 17.0202 | 31.3489 | 31.4019   | 19.7123 |
  | 1.7284        | 8.0   | 164344 | 1.7443          | 38.384  | 17.0734 | 31.4734 | 31.5214   | 19.6688 |
  | 1.7131        | 9.0   | 184887 | 1.7445          | 38.3076 | 17.0543 | 31.4168 | 31.4559   | 19.6562 |
  | 1.6869        | 10.0  | 205430 | 1.7450          | 38.4651 | 17.181  | 31.5511 | 31.6061   | 19.6752 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.13.1+cpu
  - Datasets 2.8.0
  - Tokenizers 0.10.3
  