readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-cnn
    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: 33.2082
  ---
  
  <!-- 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
  
  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: 1.8436
  - Rouge1: 33.2082
  - Rouge2: 16.798
  - Rougel: 28.9573
  - Rougelsum: 31.1044
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 2.3793        | 1.0   | 359  | 1.8885          | 33.0321 | 16.7798 | 28.9367 | 30.9509   |
  | 2.1432        | 2.0   | 718  | 1.8481          | 33.1559 | 16.8557 | 29.015  | 31.1122   |
  | 2.0571        | 3.0   | 1077 | 1.8391          | 32.99   | 16.716  | 28.8118 | 30.9178   |
  | 2.0001        | 4.0   | 1436 | 1.8357          | 33.0543 | 16.6731 | 28.8375 | 30.9604   |
  | 1.9609        | 5.0   | 1795 | 1.8437          | 33.1019 | 16.7576 | 28.8669 | 31.001    |
  | 1.925         | 6.0   | 2154 | 1.8402          | 33.1388 | 16.7539 | 28.8887 | 31.0262   |
  | 1.9036        | 7.0   | 2513 | 1.8423          | 33.1825 | 16.759  | 28.9154 | 31.0656   |
  | 1.8821        | 8.0   | 2872 | 1.8436          | 33.2082 | 16.798  | 28.9573 | 31.1044   |
  
  
  ### Framework versions
  
  - Transformers 4.14.0
  - Pytorch 1.5.0
  - Datasets 2.3.2
  - Tokenizers 0.10.3
  