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: 3.0255
  - Rouge1: 17.469
  - Rouge2: 8.5134
  - Rougel: 17.1167
  - Rougelsum: 17.2481
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 8.094         | 1.0   | 1209 | 3.2933          | 12.7976 | 5.1617 | 12.4199 | 12.5113   |
  | 3.9263        | 2.0   | 2418 | 3.1487          | 16.2082 | 8.3215 | 15.744  | 15.807    |
  | 3.599         | 3.0   | 3627 | 3.0789          | 16.9706 | 8.2425 | 16.3972 | 16.4067   |
  | 3.429         | 4.0   | 4836 | 3.0492          | 17.2122 | 8.7398 | 16.7892 | 16.795    |
  | 3.3279        | 5.0   | 6045 | 3.0384          | 17.5381 | 8.7438 | 17.0764 | 17.1831   |
  | 3.2518        | 6.0   | 7254 | 3.0343          | 17.0966 | 8.5622 | 16.7016 | 16.8022   |
  | 3.2084        | 7.0   | 8463 | 3.0255          | 16.7713 | 8.0472 | 16.3159 | 16.4091   |
  | 3.1839        | 8.0   | 9672 | 3.0255          | 17.469  | 8.5134 | 17.1167 | 17.2481   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  