readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-12-6-finetuned-roundup-4-4
    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. -->
  
  # distilbart-cnn-12-6-finetuned-roundup-4-4
  
  This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9444
  - Rouge1: 53.2401
  - Rouge2: 33.8737
  - Rougel: 36.4695
  - Rougelsum: 50.8979
  - Gen Len: 141.5185
  
  ## 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: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 398  | 1.1590          | 52.4465 | 33.664  | 35.2295 | 50.0326   | 141.6852 |
  | 1.4068        | 2.0   | 796  | 1.0174          | 53.3143 | 34.1363 | 35.8354 | 51.2277   | 141.8889 |
  | 0.9247        | 3.0   | 1194 | 0.9575          | 52.7672 | 33.1797 | 35.9617 | 50.3643   | 142.0    |
  | 0.731         | 4.0   | 1592 | 0.9444          | 53.2401 | 33.8737 | 36.4695 | 50.8979   | 141.5185 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  