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: 3.0296
  - Rouge1: 18.0335
  - Rouge2: 8.816
  - Rougel: 17.5279
  - Rougelsum: 17.6189
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.9312        | 1.0   | 1209 | 3.2984          | 14.4268 | 6.4451 | 14.0547 | 14.1363   |
  | 3.8882        | 2.0   | 2418 | 3.1272          | 17.1618 | 8.7776 | 16.4569 | 16.5079   |
  | 3.578         | 3.0   | 3627 | 3.0798          | 17.9251 | 9.2806 | 17.4056 | 17.3871   |
  | 3.4191        | 4.0   | 4836 | 3.0671          | 17.6256 | 8.8731 | 16.975  | 17.0113   |
  | 3.3193        | 5.0   | 6045 | 3.0605          | 17.9539 | 8.7188 | 17.4034 | 17.4726   |
  | 3.2434        | 6.0   | 7254 | 3.0387          | 17.0668 | 8.2769 | 16.5612 | 16.6636   |
  | 3.208         | 7.0   | 8463 | 3.0338          | 17.2954 | 8.4547 | 16.7602 | 16.8175   |
  | 3.1812        | 8.0   | 9672 | 3.0296          | 18.0335 | 8.816  | 17.5279 | 17.6189   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  