readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-cnn-news
    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: 24.7231
  ---
  
  <!-- 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-cnn-news
  
  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: 1.8412
  - Rouge1: 24.7231
  - Rouge2: 12.292
  - Rougel: 20.5347
  - Rougelsum: 23.4668
  
  ## 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: 0.00056
  - 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 2.0318        | 1.0   | 718  | 1.8028          | 24.5415 | 12.0907 | 20.5343 | 23.3386   |
  | 1.8307        | 2.0   | 1436 | 1.8028          | 24.0965 | 11.6367 | 20.2078 | 22.8138   |
  | 1.6881        | 3.0   | 2154 | 1.8136          | 25.0822 | 12.6509 | 20.9523 | 23.8303   |
  | 1.5778        | 4.0   | 2872 | 1.8269          | 24.4271 | 11.8443 | 20.2281 | 23.0941   |
  | 1.501         | 5.0   | 3590 | 1.8412          | 24.7231 | 12.292  | 20.5347 | 23.4668   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  