readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-cnn-v2
    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: 35.154
  ---
  
  <!-- 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-v2
  
  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: 1.5474
  - Rouge1: 35.154
  - Rouge2: 18.683
  - Rougel: 30.8481
  - Rougelsum: 32.9638
  
  ## 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: 5.6e-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: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 1.8823        | 1.0   | 35890  | 1.5878          | 34.9676 | 18.4927 | 30.6753 | 32.7702   |
  | 1.7871        | 2.0   | 71780  | 1.5709          | 34.9205 | 18.5556 | 30.6514 | 32.745    |
  | 1.7507        | 3.0   | 107670 | 1.5586          | 34.9825 | 18.4964 | 30.6724 | 32.7644   |
  | 1.7253        | 4.0   | 143560 | 1.5584          | 35.074  | 18.6171 | 30.8007 | 32.9132   |
  | 1.705         | 5.0   | 179450 | 1.5528          | 35.023  | 18.5787 | 30.7014 | 32.8396   |
  | 1.6894        | 6.0   | 215340 | 1.5518          | 35.0583 | 18.6754 | 30.791  | 32.8814   |
  | 1.6776        | 7.0   | 251230 | 1.5468          | 35.2236 | 18.6812 | 30.8944 | 33.0362   |
  | 1.6687        | 8.0   | 287120 | 1.5474          | 35.154  | 18.683  | 30.8481 | 32.9638   |
  
  
  ### Framework versions
  
  - Transformers 4.14.0
  - Pytorch 1.5.0
  - Datasets 2.3.2
  - Tokenizers 0.10.3
  