readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distill-pegasus-cnn-arxiv-pubmed-v3-e16
    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. -->
  
  # distill-pegasus-cnn-arxiv-pubmed-v3-e16
  
  This model is a fine-tuned version of [theojolliffe/distill-pegasus-cnn-arxiv-pubmed](https://huggingface.co/theojolliffe/distill-pegasus-cnn-arxiv-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4922
  - Rouge1: 53.3238
  - Rouge2: 36.6165
  - Rougel: 38.9255
  - Rougelsum: 50.4853
  - Gen Len: 125.7407
  
  ## 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: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | 2.7655        | 1.0   | 795   | 2.1110          | 49.0541 | 29.7039 | 33.8403 | 44.2825   | 126.1296 |
  | 2.2882        | 2.0   | 1590  | 1.9469          | 48.4651 | 30.1425 | 33.9702 | 44.3518   | 125.7778 |
  | 2.1958        | 3.0   | 2385  | 1.8079          | 49.2302 | 31.0952 | 34.4448 | 45.5764   | 125.7778 |
  | 2.0221        | 4.0   | 3180  | 1.7501          | 48.1928 | 29.9098 | 33.0587 | 44.6023   | 125.3148 |
  | 1.9078        | 5.0   | 3975  | 1.6677          | 49.697  | 31.671  | 34.3162 | 46.5108   | 125.5185 |
  | 1.8624        | 6.0   | 4770  | 1.6393          | 49.6517 | 31.7371 | 35.2019 | 46.2846   | 125.6852 |
  | 1.7853        | 7.0   | 5565  | 1.6038          | 50.3151 | 33.0952 | 36.0028 | 47.3894   | 125.6852 |
  | 1.7513        | 8.0   | 6360  | 1.5717          | 50.299  | 33.038  | 35.6841 | 47.4086   | 124.5556 |
  | 1.7026        | 9.0   | 7155  | 1.5570          | 51.6216 | 34.7609 | 37.5598 | 48.5247   | 124.7037 |
  | 1.6999        | 10.0  | 7950  | 1.5365          | 51.0888 | 34.2642 | 37.0603 | 48.5712   | 125.3519 |
  | 1.6832        | 11.0  | 8745  | 1.5249          | 51.3422 | 34.2941 | 37.7111 | 48.556    | 124.9259 |
  | 1.6093        | 12.0  | 9540  | 1.5092          | 51.4622 | 34.6397 | 38.1768 | 48.6346   | 124.8889 |
  | 1.6049        | 13.0  | 10335 | 1.5002          | 52.2463 | 35.4629 | 38.2049 | 49.4066   | 124.7963 |
  | 1.5904        | 14.0  | 11130 | 1.4957          | 51.6498 | 34.9739 | 38.4215 | 48.9704   | 125.0185 |
  | 1.5963        | 15.0  | 11925 | 1.4920          | 52.769  | 35.9563 | 38.4861 | 49.9185   | 125.6481 |
  | 1.5742        | 16.0  | 12720 | 1.4922          | 53.3238 | 36.6165 | 38.9255 | 50.4853   | 125.7407 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  