readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-med-term-mlm
    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-mlm
  
  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: 0.2506
  - Rouge2 Precision: 0.8338
  - Rouge2 Recall: 0.6005
  - Rouge2 Fmeasure: 0.6775
  
  ## 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.3426        | 1.0   | 15827 | 0.3029          | 0.8184           | 0.5913        | 0.6664          |
  | 0.2911        | 2.0   | 31654 | 0.2694          | 0.8278           | 0.5963        | 0.6727          |
  | 0.2571        | 3.0   | 47481 | 0.2549          | 0.8318           | 0.5985        | 0.6753          |
  | 0.2303        | 4.0   | 63308 | 0.2506          | 0.8338           | 0.6005        | 0.6775          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  