readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-cnndm1
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: cnn_dailymail
        type: cnn_dailymail
        args: 3.0.0
      metrics:
      - name: Rouge1
        type: rouge
        value: 24.4246
  ---
  
  <!-- 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-cnndm1
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6853
  - Rouge1: 24.4246
  - Rouge2: 11.6944
  - Rougel: 20.1717
  - Rougelsum: 23.0424
  - Gen Len: 18.9996
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.912         | 0.14  | 5000  | 1.7167          | 24.4232 | 11.7049 | 20.1758 | 23.0345   | 18.9997 |
  | 1.8784        | 0.28  | 10000 | 1.7018          | 24.4009 | 11.6918 | 20.1561 | 23.0073   | 18.9997 |
  | 1.8628        | 0.42  | 15000 | 1.6934          | 24.385  | 11.683  | 20.1285 | 22.9823   | 18.9997 |
  | 1.8594        | 0.56  | 20000 | 1.6902          | 24.4407 | 11.6835 | 20.1734 | 23.0369   | 18.9996 |
  | 1.8537        | 0.7   | 25000 | 1.6864          | 24.3635 | 11.658  | 20.1318 | 22.9782   | 18.9993 |
  | 1.8505        | 0.84  | 30000 | 1.6856          | 24.4267 | 11.6991 | 20.1629 | 23.0361   | 18.9994 |
  | 1.8505        | 0.98  | 35000 | 1.6853          | 24.4246 | 11.6944 | 20.1717 | 23.0424   | 18.9996 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  