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: 3.0183
  - Rouge1: 16.8462
  - Rouge2: 7.9926
  - Rougel: 16.7138
  - Rougelsum: 16.7353
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 3.6757        | 1.0   | 1209 | 3.2206          | 17.7063 | 9.0094 | 17.1467 | 17.1168   |
  | 3.6404        | 2.0   | 2418 | 3.0712          | 16.3983 | 7.5945 | 16.0944 | 15.9995   |
  | 3.4255        | 3.0   | 3627 | 3.0459          | 17.8576 | 9.1951 | 17.4539 | 17.4929   |
  | 3.3127        | 4.0   | 4836 | 3.0397          | 16.9239 | 7.8104 | 16.6155 | 16.585    |
  | 3.2325        | 5.0   | 6045 | 3.0406          | 16.8228 | 8.1594 | 16.6843 | 16.6554   |
  | 3.1674        | 6.0   | 7254 | 3.0252          | 17.1619 | 8.4048 | 17.0407 | 17.0515   |
  | 3.1355        | 7.0   | 8463 | 3.0226          | 17.164  | 8.2978 | 17.0445 | 17.1064   |
  | 3.1118        | 8.0   | 9672 | 3.0183          | 16.8462 | 7.9926 | 16.7138 | 16.7353   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  