readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-paraphrase-pubmed-1.1
    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-paraphrase-pubmed-1.1
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4236
  - Rouge2 Precision: 0.8482
  - Rouge2 Recall: 0.673
  - Rouge2 Fmeasure: 0.7347
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.6534        | 1.0   | 663  | 0.4641          | 0.8448           | 0.6691        | 0.7313          |
  | 0.5078        | 2.0   | 1326 | 0.4398          | 0.8457           | 0.6719        | 0.7333          |
  | 0.4367        | 3.0   | 1989 | 0.4274          | 0.847            | 0.6717        | 0.7335          |
  | 0.3575        | 4.0   | 2652 | 0.4149          | 0.8481           | 0.6733        | 0.735           |
  | 0.3319        | 5.0   | 3315 | 0.4170          | 0.8481           | 0.6724        | 0.7343          |
  | 0.3179        | 6.0   | 3978 | 0.4264          | 0.8484           | 0.6733        | 0.735           |
  | 0.2702        | 7.0   | 4641 | 0.4207          | 0.8489           | 0.6732        | 0.7353          |
  | 0.2606        | 8.0   | 5304 | 0.4205          | 0.8487           | 0.6725        | 0.7347          |
  | 0.2496        | 9.0   | 5967 | 0.4247          | 0.8466           | 0.6717        | 0.7334          |
  | 0.2353        | 10.0  | 6630 | 0.4236          | 0.8482           | 0.673         | 0.7347          |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  