readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-med-term-conditional-masking-0
    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-med-term-conditional-masking-0
  
  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: 0.5041
  - Rouge2 Precision: 0.7497
  - Rouge2 Recall: 0.5246
  - Rouge2 Fmeasure: 0.5986
  
  ## 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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.6381        | 1.0   | 13915 | 0.5595          | 0.734            | 0.5152        | 0.5873          |
  | 0.5429        | 2.0   | 27830 | 0.5243          | 0.7441           | 0.5225        | 0.5956          |
  | 0.5002        | 3.0   | 41745 | 0.5078          | 0.7482           | 0.5238        | 0.5976          |
  | 0.4607        | 4.0   | 55660 | 0.5041          | 0.7497           | 0.5246        | 0.5986          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  