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: 3.0295
  - Rouge1: 17.3239
  - Rouge2: 8.3252
  - Rougel: 16.9877
  - Rougelsum: 16.9491
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.5794        | 1.0   | 1209 | 3.2991          | 14.2697 | 5.8959 | 13.9629 | 14.019    |
  | 3.8873        | 2.0   | 2418 | 3.1327          | 16.4495 | 8.0475 | 16.0014 | 15.8747   |
  | 3.5776        | 3.0   | 3627 | 3.0835          | 17.5812 | 8.9516 | 17.0727 | 17.0682   |
  | 3.4167        | 4.0   | 4836 | 3.0604          | 16.8649 | 8.0349 | 16.3734 | 16.4011   |
  | 3.3178        | 5.0   | 6045 | 3.0599          | 17.4474 | 8.2552 | 17.1422 | 17.1661   |
  | 3.242         | 6.0   | 7254 | 3.0396          | 17.8629 | 8.9654 | 17.5915 | 17.5903   |
  | 3.2067        | 7.0   | 8463 | 3.0341          | 17.6749 | 8.8579 | 17.3253 | 17.3087   |
  | 3.179         | 8.0   | 9672 | 3.0295          | 17.3239 | 8.3252 | 16.9877 | 16.9491   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  