readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - super_glue
  metrics:
  - rouge
  model-index:
  - name: T5_finetuned
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: super_glue
        type: super_glue
        config: boolq
        split: train
        args: boolq
      metrics:
      - name: Rouge1
        type: rouge
        value: 79.3272
  ---
  
  <!-- 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_finetuned
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the super_glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1077
  - Rouge1: 79.3272
  - Rouge2: 0.0
  - Rougel: 79.2966
  - Rougelsum: 79.3272
  - Gen Len: 2.8269
  
  ## 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: 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: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 0.5134        | 1.0   | 590  | 0.1102          | 79.8165 | 0.0    | 79.8165 | 79.8471   | 2.7713  |
  | 0.105         | 2.0   | 1180 | 0.1049          | 80.3364 | 0.0    | 80.3364 | 80.367    | 2.6483  |
  | 0.1023        | 3.0   | 1770 | 0.1077          | 79.3272 | 0.0    | 79.2966 | 79.3272   | 2.8269  |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  