readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-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-small-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: 3.0171
  - Rouge1: 16.778
  - Rouge2: 8.0849
  - Rougel: 16.5329
  - Rougelsum: 16.4302
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 3.4297        | 1.0   | 1209 | 3.1211          | 17.6479 | 8.1669 | 17.1554 | 17.0276   |
  | 3.4217        | 2.0   | 2418 | 3.0394          | 16.4501 | 8.3991 | 16.2225 | 16.2214   |
  | 3.2701        | 3.0   | 3627 | 3.0427          | 16.3473 | 7.5173 | 16.1924 | 16.098    |
  | 3.1888        | 4.0   | 4836 | 3.0283          | 15.3718 | 6.8591 | 15.0889 | 14.9769   |
  | 3.1204        | 5.0   | 6045 | 3.0256          | 17.5963 | 8.331  | 17.1812 | 17.0733   |
  | 3.072         | 6.0   | 7254 | 3.0189          | 16.5811 | 8.1764 | 16.28   | 16.207    |
  | 3.0386        | 7.0   | 8463 | 3.0171          | 17.1018 | 8.4785 | 16.8196 | 16.7681   |
  | 3.0193        | 8.0   | 9672 | 3.0171          | 16.778  | 8.0849 | 16.5329 | 16.4302   |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  