readme: ---
  license: apache-2.0
  tags:
  - 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: 3.0283
  - Rouge1: 17.6736
  - Rouge2: 8.5399
  - Rougel: 17.4107
  - Rougelsum: 17.3637
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 3.7032        | 1.0   | 1209 | 3.1958          | 16.1227 | 7.4852 | 15.2662 | 15.3552   |
  | 3.6502        | 2.0   | 2418 | 3.1103          | 17.2284 | 8.1626 | 16.757  | 16.6583   |
  | 3.4365        | 3.0   | 3627 | 3.0698          | 17.2326 | 8.7096 | 17.0961 | 16.9705   |
  | 3.312         | 4.0   | 4836 | 3.0324          | 16.9472 | 8.1386 | 16.6025 | 16.6126   |
  | 3.2343        | 5.0   | 6045 | 3.0385          | 17.8752 | 8.0578 | 17.4985 | 17.5298   |
  | 3.1661        | 6.0   | 7254 | 3.0334          | 17.8822 | 8.5243 | 17.5825 | 17.5242   |
  | 3.1305        | 7.0   | 8463 | 3.0289          | 17.8187 | 8.124  | 17.4815 | 17.4688   |
  | 3.1039        | 8.0   | 9672 | 3.0283          | 17.6736 | 8.5399 | 17.4107 | 17.3637   |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu102
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  