readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-paraphrase
    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-paraphrase
  
  This model is a fine-tuned version of [Vamsi/T5_Paraphrase_Paws](https://huggingface.co/Vamsi/T5_Paraphrase_Paws) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0455
  - Rouge2 Precision: 0.5933
  - Rouge2 Recall: 0.36
  - Rouge2 Fmeasure: 0.4202
  
  ## 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: 0.0001
  - 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | No log        | 1.0   | 34   | 0.0918          | 0.5469           | 0.324         | 0.3811          |
  | No log        | 2.0   | 68   | 0.0700          | 0.5567           | 0.3245        | 0.3836          |
  | No log        | 3.0   | 102  | 0.0616          | 0.5744           | 0.3407        | 0.3986          |
  | No log        | 4.0   | 136  | 0.0564          | 0.5677           | 0.3334        | 0.3935          |
  | No log        | 5.0   | 170  | 0.0518          | 0.5774           | 0.3389        | 0.4004          |
  | No log        | 6.0   | 204  | 0.0499          | 0.583            | 0.3427        | 0.4042          |
  | No log        | 7.0   | 238  | 0.0481          | 0.59             | 0.3457        | 0.4082          |
  | No log        | 8.0   | 272  | 0.0466          | 0.5653           | 0.3316        | 0.3916          |
  | No log        | 9.0   | 306  | 0.0451          | 0.5901           | 0.3511        | 0.4123          |
  | No log        | 10.0  | 340  | 0.0449          | 0.6079           | 0.3572        | 0.423           |
  | No log        | 11.0  | 374  | 0.0451          | 0.6139           | 0.3634        | 0.4273          |
  | No log        | 12.0  | 408  | 0.0446          | 0.5903           | 0.3574        | 0.4134          |
  | No log        | 13.0  | 442  | 0.0443          | 0.6077           | 0.3587        | 0.4218          |
  | No log        | 14.0  | 476  | 0.0439          | 0.5921           | 0.3657        | 0.4235          |
  | 0.1621        | 15.0  | 510  | 0.0442          | 0.6135           | 0.3758        | 0.4395          |
  | 0.1621        | 16.0  | 544  | 0.0449          | 0.5744           | 0.3473        | 0.4054          |
  | 0.1621        | 17.0  | 578  | 0.0447          | 0.5623           | 0.3324        | 0.3917          |
  | 0.1621        | 18.0  | 612  | 0.0449          | 0.5877           | 0.3569        | 0.4165          |
  | 0.1621        | 19.0  | 646  | 0.0452          | 0.5845           | 0.3542        | 0.4138          |
  | 0.1621        | 20.0  | 680  | 0.0452          | 0.5909           | 0.3577        | 0.4189          |
  | 0.1621        | 21.0  | 714  | 0.0452          | 0.5907           | 0.3567        | 0.4179          |
  | 0.1621        | 22.0  | 748  | 0.0453          | 0.5909           | 0.3577        | 0.4189          |
  | 0.1621        | 23.0  | 782  | 0.0453          | 0.6002           | 0.367         | 0.427           |
  | 0.1621        | 24.0  | 816  | 0.0453          | 0.5958           | 0.3642        | 0.4242          |
  | 0.1621        | 25.0  | 850  | 0.0452          | 0.5915           | 0.3582        | 0.4182          |
  | 0.1621        | 26.0  | 884  | 0.0451          | 0.5933           | 0.36          | 0.4202          |
  | 0.1621        | 27.0  | 918  | 0.0454          | 0.5985           | 0.3625        | 0.4238          |
  | 0.1621        | 28.0  | 952  | 0.0453          | 0.5941           | 0.3608        | 0.4211          |
  | 0.1621        | 29.0  | 986  | 0.0454          | 0.5933           | 0.36          | 0.4202          |
  | 0.011         | 30.0  | 1020 | 0.0455          | 0.5933           | 0.36          | 0.4202          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  