readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-mlm-pubmed-15
    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-15
  
  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: 0.4822
  - Rouge2 Precision: 0.7578
  - Rouge2 Recall: 0.5933
  - Rouge2 Fmeasure: 0.6511
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.7006        | 1.0   | 663  | 0.5062          | 0.7492           | 0.5855        | 0.6434          |
  | 0.5709        | 2.0   | 1326 | 0.4811          | 0.7487           | 0.5879        | 0.6447          |
  | 0.5011        | 3.0   | 1989 | 0.4734          | 0.7541           | 0.5906        | 0.6483          |
  | 0.4164        | 4.0   | 2652 | 0.4705          | 0.7515           | 0.5876        | 0.6452          |
  | 0.3888        | 5.0   | 3315 | 0.4703          | 0.7555           | 0.5946        | 0.6515          |
  | 0.3655        | 6.0   | 3978 | 0.4725          | 0.7572           | 0.5943        | 0.6516          |
  | 0.319         | 7.0   | 4641 | 0.4733          | 0.7557           | 0.5911        | 0.6491          |
  | 0.3089        | 8.0   | 5304 | 0.4792          | 0.7577           | 0.5936        | 0.6513          |
  | 0.2907        | 9.0   | 5967 | 0.4799          | 0.7577           | 0.5931        | 0.6509          |
  | 0.275         | 10.0  | 6630 | 0.4822          | 0.7578           | 0.5933        | 0.6511          |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  