readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-small-finetuned-vitrinaTest1
    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-vitrinaTest1
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.9784
  - Rouge2 Precision: 0.1556
  - Rouge2 Recall: 0.11
  - Rouge2 Fmeasure: 0.1243
  
  ## 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: 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | No log        | 1.0   | 50   | 11.7400         | 0.0162           | 0.0139        | 0.0148          |
  | No log        | 2.0   | 100  | 4.9676          | 0.0661           | 0.0397        | 0.0471          |
  | No log        | 3.0   | 150  | 4.3307          | 0.1161           | 0.0757        | 0.0881          |
  | No log        | 4.0   | 200  | 4.0594          | 0.155            | 0.1085        | 0.1235          |
  | No log        | 5.0   | 250  | 3.9784          | 0.1556           | 0.11          | 0.1243          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  