readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-small-paraphrasing-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. -->
  
  # t5-small-paraphrasing-mlm
  
  This model is a fine-tuned version of [gayanin/t5-small-paraphrase-pubmed](https://huggingface.co/gayanin/t5-small-paraphrase-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7030
  - Rouge2 Precision: 0.6576
  - Rouge2 Recall: 0.4712
  - Rouge2 Fmeasure: 0.532
  
  ## 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.9215        | 1.0   | 13833  | 0.8050          | 0.6352           | 0.454         | 0.5131          |
  | 0.855         | 2.0   | 27666  | 0.7679          | 0.6411           | 0.4589        | 0.5184          |
  | 0.8387        | 3.0   | 41499  | 0.7464          | 0.6464           | 0.4626        | 0.5226          |
  | 0.8267        | 4.0   | 55332  | 0.7315          | 0.6513           | 0.4671        | 0.5273          |
  | 0.7879        | 5.0   | 69165  | 0.7217          | 0.6534           | 0.4687        | 0.529           |
  | 0.7738        | 6.0   | 82998  | 0.7142          | 0.6548           | 0.4688        | 0.5295          |
  | 0.7793        | 7.0   | 96831  | 0.7094          | 0.6553           | 0.4694        | 0.53            |
  | 0.7654        | 8.0   | 110664 | 0.7056          | 0.6573           | 0.4704        | 0.5313          |
  | 0.7675        | 9.0   | 124497 | 0.7036          | 0.6577           | 0.4712        | 0.532           |
  | 0.7662        | 10.0  | 138330 | 0.7030          | 0.6576           | 0.4712        | 0.532           |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  