readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: t5-v1_1-small-finetuned-cnn_dailymail
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: cnn_dailymail
        type: cnn_dailymail
        config: 3.0.0
        split: train
        args: 3.0.0
      metrics:
      - name: Rouge1
        type: rouge
        value: 0.3362804924711526
  ---
  
  <!-- 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-v1_1-small-finetuned-cnn_dailymail
  
  This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the cnn_dailymail dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7290
  - Rouge1: 0.3363
  - Rouge2: 0.1736
  - Rougel: 0.2951
  - Rougelsum: 0.3151
  
  ## 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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|
  | 2.7338        | 1.0   | 35890  | 1.8390          | 0.3278 | 0.1658 | 0.2876 | 0.3064    |
  | 2.3233        | 2.0   | 71780  | 1.7779          | 0.3335 | 0.1713 | 0.2924 | 0.3124    |
  | 2.2253        | 3.0   | 107670 | 1.7428          | 0.3348 | 0.1728 | 0.2941 | 0.3138    |
  | 2.1797        | 4.0   | 143560 | 1.7290          | 0.3363 | 0.1736 | 0.2951 | 0.3151    |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  