readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-amazon-en-es-Resumen-2
    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-Resumen-2
  
  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: 3.0910
  - Rouge1: 16.3799
  - Rouge2: 7.6088
  - Rougel: 15.9886
  - Rougelsum: 16.1691
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 7.004         | 1.0   | 1209 | 3.3408          | 13.3874 | 5.2828 | 12.9812 | 12.9666   |
  | 3.9036        | 2.0   | 2418 | 3.2286          | 15.9158 | 7.7591 | 15.2863 | 15.3932   |
  | 3.598         | 3.0   | 3627 | 3.1778          | 16.0628 | 7.1178 | 15.1227 | 15.2487   |
  | 3.4228        | 4.0   | 4836 | 3.1147          | 15.9998 | 7.6239 | 15.3691 | 15.4711   |
  | 3.3212        | 5.0   | 6045 | 3.1049          | 16.5369 | 7.743  | 16.2272 | 16.3427   |
  | 3.2658        | 6.0   | 7254 | 3.0974          | 17.4125 | 8.0961 | 17.0223 | 17.136    |
  | 3.2105        | 7.0   | 8463 | 3.0911          | 16.5786 | 7.7369 | 16.1889 | 16.3189   |
  | 3.184         | 8.0   | 9672 | 3.0910          | 16.3799 | 7.6088 | 15.9886 | 16.1691   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  