readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: cnn_dailymail-summarization-t5-small-2022-09-08
    results:
    - task:
        name: Summarization
        type: summarization
      dataset:
        name: cnn_dailymail 3.0.0
        type: cnn_dailymail
        args: 3.0.0
      metrics:
      - name: Rouge1
        type: rouge
        value: 41.4235
  ---
  
  <!-- 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. -->
  
  # cnn_dailymail-summarization-t5-small-2022-09-08
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail 3.0.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6455
  - Rouge1: 41.4235
  - Rouge2: 19.0263
  - Rougel: 29.2892
  - Rougelsum: 38.6338
  - Gen Len: 73.7273
  
  ## 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: 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: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.8435        | 0.28  | 10000  | 1.6998          | 24.3321 | 11.599  | 20.1028 | 22.9562   | 18.9997 |
  | 1.8464        | 0.56  | 20000  | 1.6814          | 24.4483 | 11.6789 | 20.1798 | 23.0508   | 18.9996 |
  | 1.8332        | 0.84  | 30000  | 1.6738          | 24.5531 | 11.7949 | 20.2834 | 23.1588   | 18.9994 |
  | 1.8054        | 1.11  | 40000  | 1.6636          | 24.6194 | 11.843  | 20.3375 | 23.2259   | 18.9991 |
  | 1.7958        | 1.39  | 50000  | 1.6597          | 24.5017 | 11.7755 | 20.2439 | 23.1148   | 18.9998 |
  | 1.8095        | 1.67  | 60000  | 1.6546          | 24.5126 | 11.8043 | 20.2603 | 23.1175   | 18.9999 |
  | 1.8127        | 1.95  | 70000  | 1.6521          | 24.4845 | 11.8136 | 20.2557 | 23.1089   | 18.9999 |
  | 1.7952        | 2.23  | 80000  | 1.6488          | 24.6217 | 11.8877 | 20.3555 | 23.2514   | 18.9996 |
  | 1.7863        | 2.51  | 90000  | 1.6477          | 24.5616 | 11.8489 | 20.3021 | 23.1754   | 18.9996 |
  | 1.7824        | 2.79  | 100000 | 1.6464          | 24.5852 | 11.8531 | 20.3172 | 23.2089   | 18.9998 |
  
  
  ### Framework versions
  
  - Transformers 4.22.0.dev0
  - Pytorch 1.12.1+cu102
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  