readme: ---
  license: apache-2.0
  language:
  - en
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-base-finetuned-turk-text-simplification
    results: []
  widget:
  - text: "simplify: the incident has been the subject of numerous reports as to ethics in scholarship ."
  - text: "simplify: the historical method comprises the techniques and guidelines by which historians use primary sources and other evidence to research and then to write history ."
  - text: "simplify: none of the authors , contributors , sponsors , administrators , vandals , or anyone else connected with wikipedia , in any way whatsoever , can be responsible for your use of the information contained in or linked from these web pages ."
  - text: "simplify: oregano is an indispensable ingredient in greek cuisine ."
  
  ---
  
  <!-- 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 (base) finetuned-turk-text-simplification
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0913
  - Rouge2 Precision: 0.6559
  - Rouge2 Recall: 0.4369
  - Rouge2 Fmeasure: 0.5034
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.0955        | 1.0   | 2000  | 0.0948          | 0.656            | 0.4404        | 0.5063          |
  | 0.0872        | 2.0   | 4000  | 0.0913          | 0.6559           | 0.4369        | 0.5034          |
  | 0.0877        | 3.0   | 6000  | 0.0913          | 0.6559           | 0.4369        | 0.5034          |
  | 0.0881        | 4.0   | 8000  | 0.0913          | 0.6559           | 0.4369        | 0.5034          |
  | 0.0867        | 5.0   | 10000 | 0.0913          | 0.6559           | 0.4369        | 0.5034          |
  
  
  ### Framework versions
  
  - Transformers 4.22.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  