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: 3.0318
  - Rouge1: 0.1806
  - Rouge2: 0.0917
  - Rougel: 0.1765
  - Rougelsum: 0.1766
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 6.6121        | 1.0   | 1209 | 3.2969          | 0.1522 | 0.0635 | 0.1476 | 0.147     |
  | 3.901         | 2.0   | 2418 | 3.1307          | 0.1672 | 0.0821 | 0.1604 | 0.1602    |
  | 3.5788        | 3.0   | 3627 | 3.0910          | 0.1804 | 0.0922 | 0.1748 | 0.1751    |
  | 3.4198        | 4.0   | 4836 | 3.0646          | 0.1717 | 0.0813 | 0.167  | 0.1664    |
  | 3.321         | 5.0   | 6045 | 3.0659          | 0.1782 | 0.0877 | 0.1759 | 0.1756    |
  | 3.2441        | 6.0   | 7254 | 3.0407          | 0.1785 | 0.088  | 0.1755 | 0.1751    |
  | 3.2075        | 7.0   | 8463 | 3.0356          | 0.1789 | 0.09   | 0.1743 | 0.1747    |
  | 3.1803        | 8.0   | 9672 | 3.0318          | 0.1806 | 0.0917 | 0.1765 | 0.1766    |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  