readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - samsum
  metrics:
  - rouge
  model-index:
  - name: t5-v1_1-small-finetuned-samsum
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: samsum
        type: samsum
        config: samsum
        split: train
        args: samsum
      metrics:
      - name: Rouge1
        type: rouge
        value: 0.40608242084369006
  ---
  
  <!-- 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-samsum
  
  This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the samsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0053
  - Rouge1: 0.4061
  - Rouge2: 0.1804
  - Rougel: 0.3478
  - Rougelsum: 0.3774
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 3.9788        | 1.0   | 1842 | 2.2499          | 0.3743 | 0.1569 | 0.3191 | 0.3486    |
  | 2.9091        | 2.0   | 3684 | 2.1052          | 0.3875 | 0.1680 | 0.3329 | 0.3607    |
  | 2.6807        | 3.0   | 5526 | 2.0270          | 0.4009 | 0.1778 | 0.3439 | 0.3734    |
  | 2.5917        | 4.0   | 7368 | 2.0053          | 0.4061 | 0.1804 | 0.3478 | 0.3774    |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  