readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-arxiv-pubmed-v3-e12
    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-arxiv-pubmed-v3-e12
  
  This model is a fine-tuned version of [theojolliffe/distilbart-cnn-arxiv-pubmed](https://huggingface.co/theojolliffe/distilbart-cnn-arxiv-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8157
  - Rouge1: 56.7429
  - Rouge2: 41.0185
  - Rougel: 44.1014
  - Rougelsum: 54.8121
  - 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: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | 1.5037        | 1.0   | 795  | 1.0815          | 52.4727 | 33.4915 | 35.3774 | 50.1955   | 142.0    |
  | 0.8894        | 2.0   | 1590 | 0.9462          | 52.8867 | 34.0406 | 36.5249 | 50.4636   | 141.5741 |
  | 0.7037        | 3.0   | 2385 | 0.8841          | 53.7966 | 35.0969 | 38.4158 | 51.3369   | 142.0    |
  | 0.4914        | 4.0   | 3180 | 0.8437          | 52.6766 | 34.0573 | 36.8907 | 50.3088   | 142.0    |
  | 0.3945        | 5.0   | 3975 | 0.8067          | 54.3147 | 36.2081 | 39.6366 | 52.1494   | 142.0    |
  | 0.2799        | 6.0   | 4770 | 0.8403          | 54.2813 | 37.0786 | 39.9196 | 51.9176   | 141.9815 |
  | 0.2211        | 7.0   | 5565 | 0.8207          | 53.9403 | 36.517  | 39.0372 | 51.4491   | 141.9815 |
  | 0.1795        | 8.0   | 6360 | 0.8014          | 55.6607 | 39.3082 | 41.8295 | 53.4674   | 142.0    |
  | 0.1428        | 9.0   | 7155 | 0.8051          | 55.0575 | 38.823  | 41.8849 | 52.9606   | 142.0    |
  | 0.1358        | 10.0  | 7950 | 0.8149          | 56.6986 | 41.0    | 43.5207 | 54.6402   | 142.0    |
  | 0.1122        | 11.0  | 8745 | 0.8134          | 56.5416 | 40.9495 | 44.2989 | 54.5623   | 142.0    |
  | 0.0873        | 12.0  | 9540 | 0.8157          | 56.7429 | 41.0185 | 44.1014 | 54.8121   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  