readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-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. -->
  
  # bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-v3-e12
  
  This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8501
  - Rouge1: 56.1453
  - Rouge2: 40.018
  - Rougel: 43.5586
  - Rougelsum: 54.4271
  - 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: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 398  | 0.8670          | 54.4613 | 34.7958 | 36.5841 | 51.9208   | 142.0   |
  | 0.8276        | 2.0   | 796  | 0.8061          | 53.5804 | 34.5801 | 37.4643 | 51.1494   | 142.0   |
  | 0.5318        | 3.0   | 1194 | 0.8146          | 53.7541 | 34.2446 | 37.5488 | 51.2475   | 142.0   |
  | 0.3541        | 4.0   | 1592 | 0.7578          | 53.7645 | 34.874  | 38.3958 | 51.3075   | 142.0   |
  | 0.3541        | 5.0   | 1990 | 0.7778          | 55.2787 | 37.5539 | 40.5489 | 52.8514   | 142.0   |
  | 0.2386        | 6.0   | 2388 | 0.7810          | 55.2487 | 38.6522 | 41.466  | 53.379    | 142.0   |
  | 0.1652        | 7.0   | 2786 | 0.7905          | 54.3618 | 37.4987 | 40.7348 | 52.2938   | 142.0   |
  | 0.1152        | 8.0   | 3184 | 0.7934          | 54.4888 | 37.649  | 40.3582 | 52.3451   | 142.0   |
  | 0.0942        | 9.0   | 3582 | 0.8220          | 55.5489 | 39.8493 | 42.2318 | 53.727    | 142.0   |
  | 0.0942        | 10.0  | 3980 | 0.8331          | 55.7509 | 39.9491 | 43.2336 | 53.9748   | 142.0   |
  | 0.0669        | 11.0  | 4378 | 0.8298          | 57.3881 | 42.6588 | 45.4694 | 55.8334   | 142.0   |
  | 0.0531        | 12.0  | 4776 | 0.8501          | 56.1453 | 40.018  | 43.5586 | 54.4271   | 142.0   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  