readme: ---
  license: apache-2.0
  tags:
  - translation
  - 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: 17.5202
  - Rouge2: 8.4634
  - Rougel: 17.0175
  - Rougelsum: 17.0528
  
  ## 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          | 12.7563 | 5.2606 | 12.4786 | 12.4961   |
  | 3.9263        | 2.0   | 2418 | 3.1487          | 16.2314 | 8.4716 | 15.6854 | 15.7506   |
  | 3.599         | 3.0   | 3627 | 3.0789          | 16.9233 | 8.1928 | 16.2596 | 16.2522   |
  | 3.429         | 4.0   | 4836 | 3.0492          | 17.2679 | 8.7561 | 16.6685 | 16.7399   |
  | 3.3279        | 5.0   | 6045 | 3.0384          | 17.6081 | 8.6721 | 17.0546 | 17.0368   |
  | 3.2518        | 6.0   | 7254 | 3.0343          | 17.2271 | 8.504  | 16.6285 | 16.6209   |
  | 3.2084        | 7.0   | 8463 | 3.0255          | 16.7859 | 8.054  | 16.2574 | 16.2853   |
  | 3.1839        | 8.0   | 9672 | 3.0255          | 17.5202 | 8.4634 | 17.0175 | 17.0528   |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  