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: 3.0393
  - Rouge1: 17.2936
  - Rouge2: 8.0678
  - Rougel: 16.8129
  - Rougelsum: 16.9991
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.6665        | 1.0   | 1209 | 3.2917          | 13.912  | 5.595  | 13.2984 | 13.4171   |
  | 3.8961        | 2.0   | 2418 | 3.1711          | 16.2845 | 8.6033 | 15.5509 | 15.7383   |
  | 3.5801        | 3.0   | 3627 | 3.0917          | 17.316  | 8.122  | 16.697  | 16.773    |
  | 3.4258        | 4.0   | 4836 | 3.0583          | 16.1347 | 7.7829 | 15.6475 | 15.7804   |
  | 3.3154        | 5.0   | 6045 | 3.0573          | 17.5918 | 8.7349 | 17.0537 | 17.2216   |
  | 3.2438        | 6.0   | 7254 | 3.0479          | 17.2294 | 8.0383 | 16.8141 | 16.9858   |
  | 3.2024        | 7.0   | 8463 | 3.0377          | 17.2918 | 8.139  | 16.8178 | 16.9671   |
  | 3.1745        | 8.0   | 9672 | 3.0393          | 17.2936 | 8.0678 | 16.8129 | 16.9991   |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.2
  - Tokenizers 0.11.0
  