readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-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-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: 3.0285
  - Rouge1: 16.9728
  - Rouge2: 8.2969
  - Rougel: 16.8366
  - Rougelsum: 16.851
  - Gen Len: 10.1597
  
  ## 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 | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 7.1016        | 1.0   | 1209 | 3.3069          | 13.9858 | 5.8437 | 13.6053 | 13.5125   | 8.3782  |
  | 3.898         | 2.0   | 2418 | 3.1567          | 16.6706 | 8.6393 | 16.2882 | 16.2249   | 9.7521  |
  | 3.5915        | 3.0   | 3627 | 3.0928          | 17.111  | 8.3921 | 16.9139 | 16.7805   | 10.3445 |
  | 3.4174        | 4.0   | 4836 | 3.0482          | 16.9728 | 8.3066 | 16.8868 | 16.8485   | 10.3151 |
  | 3.3258        | 5.0   | 6045 | 3.0375          | 16.5972 | 8.2621 | 16.3524 | 16.3093   | 10.0672 |
  | 3.2427        | 6.0   | 7254 | 3.0232          | 17.3009 | 8.6087 | 17.0782 | 17.0105   | 10.0756 |
  | 3.2009        | 7.0   | 8463 | 3.0302          | 16.9284 | 8.6569 | 16.7885 | 16.7784   | 10.2143 |
  | 3.1838        | 8.0   | 9672 | 3.0285          | 16.9728 | 8.2969 | 16.8366 | 16.851    | 10.1597 |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.1+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  