readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-t5-summarization
    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: 24.5755
  ---
  
  <!-- 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-t5-summarization
  
  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: 1.7613
  - Rouge1: 24.5755
  - Rouge2: 11.8424
  - Rougel: 20.3031
  - Rougelsum: 23.1867
  - Gen Len: 18.9999
  
  ## 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: 6e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.9891        | 1.0   | 17945  | 1.7981          | 24.382  | 11.7099 | 20.1707 | 23.0021   | 18.9998 |
  | 1.9527        | 2.0   | 35890  | 1.7816          | 24.4884 | 11.7673 | 20.2698 | 23.1233   | 19.0    |
  | 1.9421        | 3.0   | 53835  | 1.7728          | 24.5782 | 11.8401 | 20.3343 | 23.2033   | 18.9997 |
  | 1.9298        | 4.0   | 71780  | 1.7677          | 24.566  | 11.8723 | 20.3296 | 23.1943   | 18.9999 |
  | 1.9256        | 5.0   | 89725  | 1.7619          | 24.5662 | 11.8385 | 20.3265 | 23.2016   | 18.9999 |
  | 1.9056        | 6.0   | 107670 | 1.7613          | 24.5755 | 11.8424 | 20.3031 | 23.1867   | 18.9999 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  