readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-amazon-en-es
    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: 22.6804
  ---
  
  <!-- 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. -->
  
  # mt5-small-finetuned-amazon-en-es
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the cnn_dailymail dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.4413
  - Rouge1: 22.6804
  - Rouge2: 8.3299
  - Rougel: 17.9992
  - Rougelsum: 20.7342
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 7.77          | 1.0   | 240  | 2.7230          | 17.25   | 5.629  | 14.0381 | 15.8959   |
  | 3.7586        | 2.0   | 480  | 2.5949          | 19.4577 | 6.9354 | 15.772  | 17.8773   |
  | 3.4314        | 3.0   | 720  | 2.5355          | 20.0511 | 7.6417 | 16.0889 | 18.4551   |
  | 3.2892        | 4.0   | 960  | 2.4845          | 20.3951 | 7.88   | 16.601  | 19.0048   |
  | 3.1954        | 5.0   | 1200 | 2.4612          | 20.1806 | 7.2656 | 16.2658 | 18.6222   |
  | 3.1128        | 6.0   | 1440 | 2.4544          | 22.5647 | 8.0899 | 17.8057 | 20.487    |
  | 3.103         | 7.0   | 1680 | 2.4498          | 22.7048 | 8.384  | 17.978  | 20.6871   |
  | 3.0708        | 8.0   | 1920 | 2.4413          | 22.6804 | 8.3299 | 17.9992 | 20.7342   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  