readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-arxiv-pubmed-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. -->
  
  # distilbart-cnn-arxiv-pubmed-pubmed-v3-e16
  
  This model is a fine-tuned version of [theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed](https://huggingface.co/theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8306
  - Rouge1: 56.4519
  - Rouge2: 41.6818
  - Rougel: 44.7833
  - Rougelsum: 54.6359
  - Gen Len: 141.9815
  
  ## 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: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 398  | 1.1157          | 50.9487 | 31.3005 | 34.0145 | 48.6057   | 141.8519 |
  | 1.3569        | 2.0   | 796  | 0.9688          | 53.0653 | 34.1855 | 37.0759 | 50.5942   | 141.2963 |
  | 0.8704        | 3.0   | 1194 | 0.9053          | 53.9684 | 36.0388 | 38.6674 | 51.9604   | 142.0    |
  | 0.6287        | 4.0   | 1592 | 0.8515          | 54.2379 | 36.4915 | 39.1393 | 51.6991   | 141.4074 |
  | 0.6287        | 5.0   | 1990 | 0.8274          | 53.6806 | 34.8373 | 37.7369 | 51.239    | 141.6481 |
  | 0.465         | 6.0   | 2388 | 0.8486          | 55.2534 | 39.1757 | 41.6366 | 53.2989   | 141.9259 |
  | 0.3432        | 7.0   | 2786 | 0.8116          | 54.539  | 37.6314 | 40.5531 | 52.1997   | 141.3889 |
  | 0.2577        | 8.0   | 3184 | 0.7976          | 54.8212 | 36.8347 | 40.6768 | 52.7785   | 142.0    |
  | 0.204         | 9.0   | 3582 | 0.8010          | 53.9302 | 37.3523 | 40.135  | 52.139    | 141.7778 |
  | 0.204         | 10.0  | 3980 | 0.8168          | 54.3151 | 38.0665 | 42.4112 | 52.4682   | 142.0    |
  | 0.1663        | 11.0  | 4378 | 0.8171          | 54.7027 | 38.3117 | 42.0196 | 52.8821   | 142.0    |
  | 0.135         | 12.0  | 4776 | 0.8202          | 54.1035 | 37.9154 | 40.7676 | 52.2509   | 142.0    |
  | 0.1102        | 13.0  | 5174 | 0.8204          | 56.223  | 41.0947 | 44.0131 | 54.3353   | 142.0    |
  | 0.0928        | 14.0  | 5572 | 0.8280          | 56.1637 | 41.0408 | 44.2931 | 54.5488   | 142.0    |
  | 0.0928        | 15.0  | 5970 | 0.8273          | 56.2608 | 41.3855 | 44.4432 | 54.5778   | 142.0    |
  | 0.0847        | 16.0  | 6368 | 0.8306          | 56.4519 | 41.6818 | 44.7833 | 54.6359   | 141.9815 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.0
  - Tokenizers 0.12.1
  