readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-large-cnn-finetuned-roundup-3-8
    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-large-cnn-finetuned-roundup-3-8
  
  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4132
  - Rouge1: 49.6606
  - Rouge2: 28.4044
  - Rougel: 31.5419
  - Rougelsum: 46.2463
  - Gen Len: 142.0
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 258  | 1.2686          | 48.8513 | 28.7007 | 31.1199 | 45.7318   | 142.0    |
  | 1.1738        | 2.0   | 516  | 1.1884          | 49.8072 | 28.9817 | 31.3611 | 46.9639   | 141.6875 |
  | 1.1738        | 3.0   | 774  | 1.1970          | 49.3865 | 28.3426 | 30.0945 | 46.4681   | 141.3438 |
  | 0.7069        | 4.0   | 1032 | 1.1984          | 50.6743 | 29.4728 | 31.5364 | 47.989    | 141.7188 |
  | 0.7069        | 5.0   | 1290 | 1.2494          | 49.4461 | 28.9295 | 31.0334 | 46.6611   | 142.0    |
  | 0.4618        | 6.0   | 1548 | 1.2954          | 50.6789 | 30.2783 | 32.1932 | 47.5929   | 142.0    |
  | 0.4618        | 7.0   | 1806 | 1.3638          | 49.9476 | 30.223  | 32.4346 | 46.7383   | 142.0    |
  | 0.3293        | 8.0   | 2064 | 1.4132          | 49.6606 | 28.4044 | 31.5419 | 46.2463   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  