readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wiki_auto_asset_turk
  model-index:
  - name: t5-small-finetuned-text-simplification
    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-finetuned-text-simplification
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wiki_auto_asset_turk dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1217
  - Rouge2 Precision: 0.5537
  - Rouge2 Recall: 0.4251
  - Rouge2 Fmeasure: 0.4616
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.1604        | 1.0   | 15119 | 0.1156          | 0.5567           | 0.4266        | 0.4633          |
  | 0.1573        | 2.0   | 30238 | 0.1163          | 0.5534           | 0.4258        | 0.462           |
  | 0.1552        | 3.0   | 45357 | 0.1197          | 0.5527           | 0.4244        | 0.4608          |
  | 0.1514        | 4.0   | 60476 | 0.1214          | 0.5528           | 0.4257        | 0.4617          |
  | 0.1524        | 5.0   | 75595 | 0.1217          | 0.5537           | 0.4251        | 0.4616          |
  
  
  ### Framework versions
  
  - Transformers 4.22.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  