readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-12-6-finetuned-roundup-4-8
    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. -->
  
  # distilbart-cnn-12-6-finetuned-roundup-4-8
  
  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: 0.8447
  - Rouge1: 54.3326
  - Rouge2: 36.1031
  - Rougel: 38.842
  - Rougelsum: 51.7632
  - 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   | 398  | 1.1572          | 51.6618 | 32.7542 | 34.8631 | 49.2691   | 141.3333 |
  | 1.405         | 2.0   | 796  | 1.0039          | 52.2029 | 32.6704 | 34.4948 | 50.1141   | 142.0    |
  | 0.9039        | 3.0   | 1194 | 0.9300          | 53.2839 | 34.3928 | 36.8971 | 51.1148   | 142.0    |
  | 0.6705        | 4.0   | 1592 | 0.8708          | 52.5229 | 33.8116 | 36.9664 | 50.0067   | 142.0    |
  | 0.6705        | 5.0   | 1990 | 0.8508          | 53.4468 | 35.1394 | 38.4144 | 50.794    | 142.0    |
  | 0.5205        | 6.0   | 2388 | 0.8347          | 53.8859 | 35.1182 | 38.1126 | 51.3089   | 142.0    |
  | 0.3898        | 7.0   | 2786 | 0.8406          | 54.2293 | 36.1189 | 38.7127 | 51.6878   | 142.0    |
  | 0.3468        | 8.0   | 3184 | 0.8447          | 54.3326 | 36.1031 | 38.842  | 51.7632   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  