readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small11-finetuned-amazon-en-es
    results: []
  ---
  
  <!-- 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-small11-finetuned-amazon-en-es
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.1387
  - Rouge1: 16.9142
  - Rouge2: 8.3849
  - Rougel: 16.3047
  - Rougelsum: 16.3944
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | No log        | 1.0   | 303  | 3.8475          | 8.4475  | 2.0715 | 8.0724  | 8.1338    |
  | 7.6451        | 2.0   | 606  | 3.3229          | 13.3087 | 5.3619 | 12.9415 | 12.9456   |
  | 7.6451        | 3.0   | 909  | 3.2545          | 14.6953 | 6.0113 | 14.0407 | 14.1568   |
  | 4.0402        | 4.0   | 1212 | 3.2019          | 15.7812 | 7.9828 | 15.3358 | 15.3699   |
  | 4.0402        | 5.0   | 1515 | 3.1825          | 16.4009 | 8.0668 | 15.8856 | 15.9512   |
  | 3.7478        | 6.0   | 1818 | 3.1536          | 16.9352 | 8.4976 | 16.2737 | 16.4293   |
  | 3.7478        | 7.0   | 2121 | 3.1394          | 17.0823 | 8.4234 | 16.3758 | 16.5238   |
  | 3.6411        | 8.0   | 2424 | 3.1387          | 16.9142 | 8.3849 | 16.3047 | 16.3944   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  