readme: ---
  license: mit
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-base-cnn-xsum-wiki-swe
    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-cnn-xsum-wiki-swe
  
  This model is a fine-tuned version of [Gabriel/bart-base-cnn-xsum-swe](https://huggingface.co/Gabriel/bart-base-cnn-xsum-swe) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3884
  - Rouge1: 26.8917
  - Rouge2: 11.8254
  - Rougel: 22.6089
  - Rougelsum: 26.1492
  - Gen Len: 19.3468
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 9
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.4993        | 1.0   | 2985  | 2.3834          | 25.8959 | 10.9373 | 21.8329 | 25.2002   | 19.1416 |
  | 2.2397        | 2.0   | 5970  | 2.2939          | 26.1166 | 11.4087 | 22.2444 | 25.4752   | 19.2351 |
  | 2.0318        | 3.0   | 8955  | 2.2687          | 26.5222 | 11.6512 | 22.567  | 25.851    | 19.2384 |
  | 1.879         | 4.0   | 11940 | 2.2750          | 26.7637 | 11.7676 | 22.6674 | 26.0753   | 19.2622 |
  | 1.7532        | 5.0   | 14925 | 2.2923          | 26.8104 | 11.8724 | 22.6794 | 26.0907   | 19.3063 |
  | 1.6315        | 6.0   | 17910 | 2.3190          | 26.7758 | 11.7989 | 22.5925 | 26.032    | 19.3136 |
  | 1.5409        | 7.0   | 20895 | 2.3517          | 26.8762 | 11.8552 | 22.6694 | 26.1329   | 19.3275 |
  | 1.4711        | 8.0   | 23880 | 2.3679          | 26.899  | 11.9185 | 22.6764 | 26.1574   | 19.2994 |
  | 1.4105        | 9.0   | 26865 | 2.3884          | 26.8917 | 11.8254 | 22.6089 | 26.1492   | 19.3468 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  