readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-finetuned-pubmed
    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-finetuned-pubmed
  
  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: 1.5363
  - Rouge2 Precision: 0.3459
  - Rouge2 Recall: 0.2455
  - Rouge2 Fmeasure: 0.2731
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 1.652         | 1.0   | 1125  | 1.5087          | 0.3647           | 0.2425        | 0.2772          |
  | 1.4695        | 2.0   | 2250  | 1.5039          | 0.3448           | 0.2457        | 0.2732          |
  | 1.3714        | 3.0   | 3375  | 1.4842          | 0.3509           | 0.2474        | 0.277           |
  | 1.2734        | 4.0   | 4500  | 1.4901          | 0.3452           | 0.2426        | 0.2716          |
  | 1.1853        | 5.0   | 5625  | 1.5152          | 0.3658           | 0.2371        | 0.2744          |
  | 1.0975        | 6.0   | 6750  | 1.5133          | 0.3529           | 0.2417        | 0.2729          |
  | 1.0448        | 7.0   | 7875  | 1.5203          | 0.3485           | 0.2464        | 0.275           |
  | 0.9999        | 8.0   | 9000  | 1.5316          | 0.3437           | 0.2435        | 0.2719          |
  | 0.9732        | 9.0   | 10125 | 1.5338          | 0.3464           | 0.2446        | 0.2732          |
  | 0.954         | 10.0  | 11250 | 1.5363          | 0.3459           | 0.2455        | 0.2731          |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  