readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-small-mlm-pubmed
    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. -->
  
  # t5-small-mlm-pubmed
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8008
  - Rouge2 Precision: 0.6071
  - Rouge2 Recall: 0.4566
  - Rouge2 Fmeasure: 0.5079
  
  ## 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: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.914         | 0.75  | 500   | 0.8691          | 0.5901           | 0.4357        | 0.4879          |
  | 0.9093        | 1.51  | 1000  | 0.8646          | 0.5867           | 0.4372        | 0.488           |
  | 0.895         | 2.26  | 1500  | 0.8618          | 0.5891           | 0.4387        | 0.49            |
  | 0.8842        | 3.02  | 2000  | 0.8571          | 0.5899           | 0.4374        | 0.4891          |
  | 0.8796        | 3.77  | 2500  | 0.8544          | 0.5903           | 0.4406        | 0.4916          |
  | 0.8759        | 4.52  | 3000  | 0.8513          | 0.5921           | 0.4395        | 0.4912          |
  | 0.8621        | 5.28  | 3500  | 0.8485          | 0.5934           | 0.4413        | 0.493           |
  | 0.8613        | 6.03  | 4000  | 0.8442          | 0.5944           | 0.4428        | 0.4944          |
  | 0.8537        | 6.79  | 4500  | 0.8406          | 0.594            | 0.4414        | 0.4932          |
  | 0.8518        | 7.54  | 5000  | 0.8399          | 0.5956           | 0.4424        | 0.4945          |
  | 0.8438        | 8.3   | 5500  | 0.8365          | 0.5953           | 0.4452        | 0.4964          |
  | 0.8339        | 9.05  | 6000  | 0.8353          | 0.5983           | 0.4468        | 0.4983          |
  | 0.8307        | 9.8   | 6500  | 0.8331          | 0.5979           | 0.4461        | 0.4976          |
  | 0.8328        | 10.56 | 7000  | 0.8304          | 0.5975           | 0.4465        | 0.4979          |
  | 0.8263        | 11.31 | 7500  | 0.8283          | 0.5977           | 0.4467        | 0.4981          |
  | 0.8168        | 12.07 | 8000  | 0.8267          | 0.5971           | 0.4463        | 0.4976          |
  | 0.8165        | 12.82 | 8500  | 0.8248          | 0.5969           | 0.4462        | 0.4976          |
  | 0.8084        | 13.57 | 9000  | 0.8245          | 0.6018           | 0.4527        | 0.5035          |
  | 0.8136        | 14.33 | 9500  | 0.8219          | 0.6023           | 0.4509        | 0.5023          |
  | 0.8073        | 15.08 | 10000 | 0.8206          | 0.6002           | 0.4486        | 0.5001          |
  | 0.808         | 15.84 | 10500 | 0.8185          | 0.6009           | 0.4506        | 0.5019          |
  | 0.8027        | 16.59 | 11000 | 0.8173          | 0.5978           | 0.4478        | 0.4989          |
  | 0.8061        | 17.35 | 11500 | 0.8169          | 0.6022           | 0.4513        | 0.5026          |
  | 0.7922        | 18.1  | 12000 | 0.8152          | 0.6016           | 0.4501        | 0.5016          |
  | 0.7928        | 18.85 | 12500 | 0.8141          | 0.6009           | 0.45          | 0.5012          |
  | 0.7909        | 19.61 | 13000 | 0.8143          | 0.6019           | 0.4521        | 0.5028          |
  | 0.7909        | 20.36 | 13500 | 0.8115          | 0.5997           | 0.4505        | 0.5011          |
  | 0.7949        | 21.12 | 14000 | 0.8115          | 0.6043           | 0.4536        | 0.5048          |
  | 0.7853        | 21.87 | 14500 | 0.8095          | 0.6033           | 0.4527        | 0.5038          |
  | 0.7819        | 22.62 | 15000 | 0.8095          | 0.6054           | 0.4541        | 0.5056          |
  | 0.7828        | 23.38 | 15500 | 0.8075          | 0.6036           | 0.453         | 0.5042          |
  | 0.787         | 24.13 | 16000 | 0.8068          | 0.6031           | 0.4528        | 0.504           |
  | 0.7739        | 24.89 | 16500 | 0.8072          | 0.6043           | 0.4529        | 0.5045          |
  | 0.7782        | 25.64 | 17000 | 0.8073          | 0.606            | 0.4551        | 0.5063          |
  | 0.7772        | 26.4  | 17500 | 0.8063          | 0.6055           | 0.4549        | 0.5062          |
  | 0.7718        |