readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-mlm-pubmed-35
    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-35
  
  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: 0.9359
  - Rouge2 Precision: 0.5451
  - Rouge2 Recall: 0.4232
  - Rouge2 Fmeasure: 0.4666
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 1.4156        | 1.0   | 663  | 1.0366          | 0.5165           | 0.3967        | 0.4394          |
  | 1.1773        | 2.0   | 1326 | 0.9841          | 0.5354           | 0.4168        | 0.4589          |
  | 1.0894        | 3.0   | 1989 | 0.9554          | 0.5346           | 0.4133        | 0.4563          |
  | 0.9359        | 4.0   | 2652 | 0.9440          | 0.5357           | 0.4163        | 0.4587          |
  | 0.8758        | 5.0   | 3315 | 0.9340          | 0.5428           | 0.4226        | 0.465           |
  | 0.8549        | 6.0   | 3978 | 0.9337          | 0.5385           | 0.422         | 0.4634          |
  | 0.7743        | 7.0   | 4641 | 0.9330          | 0.542            | 0.422         | 0.4647          |
  | 0.7465        | 8.0   | 5304 | 0.9315          | 0.5428           | 0.4231        | 0.4654          |
  | 0.7348        | 9.0   | 5967 | 0.9344          | 0.5462           | 0.4244        | 0.4674          |
  | 0.7062        | 10.0  | 6630 | 0.9359          | 0.5451           | 0.4232        | 0.4666          |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  