readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-mlm-pubmed-medterm
    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-mlm-pubmed-medterm
  
  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: 0.0000
  - Rouge2 Precision: 0.985
  - Rouge2 Recall: 0.7208
  - Rouge2 Fmeasure: 0.8088
  
  ## 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 |
  |:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.0018        | 1.0   | 13833  | 0.0003          | 0.985            | 0.7208        | 0.8088          |
  | 0.0014        | 2.0   | 27666  | 0.0006          | 0.9848           | 0.7207        | 0.8086          |
  | 0.0009        | 3.0   | 41499  | 0.0002          | 0.9848           | 0.7207        | 0.8086          |
  | 0.0007        | 4.0   | 55332  | 0.0002          | 0.985            | 0.7208        | 0.8088          |
  | 0.0006        | 5.0   | 69165  | 0.0001          | 0.9848           | 0.7207        | 0.8087          |
  | 0.0001        | 6.0   | 82998  | 0.0002          | 0.9846           | 0.7206        | 0.8086          |
  | 0.0009        | 7.0   | 96831  | 0.0001          | 0.9848           | 0.7208        | 0.8087          |
  | 0.0           | 8.0   | 110664 | 0.0000          | 0.9848           | 0.7207        | 0.8087          |
  | 0.0001        | 9.0   | 124497 | 0.0000          | 0.985            | 0.7208        | 0.8088          |
  | 0.0           | 10.0  | 138330 | 0.0000          | 0.985            | 0.7208        | 0.8088          |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  