readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - xsum
  metrics:
  - rouge
  model-index:
  - name: t5-small-shuffled_take3-small
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: xsum
        type: xsum
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 11.883
  ---
  
  <!-- 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-shuffled_take3-small
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4505
  - Rouge1: 11.883
  - Rouge2: 9.4784
  - Rougel: 10.9978
  - Rougelsum: 11.5961
  - Gen Len: 18.9834
  
  ## 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: 6
  - eval_batch_size: 6
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:-------:|:---------:|:-------:|
  | 0.5205        | 1.0   | 34008 | 0.4505          | 11.883 | 9.4784 | 10.9978 | 11.5961   | 18.9834 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  