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: 3.0329
  - Rouge1: 16.3034
  - Rouge2: 7.8192
  - Rougel: 16.0316
  - Rougelsum: 15.9173
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 7.0891        | 1.0   | 1209 | 3.2989          | 13.8686 | 6.1132 | 13.3657 | 13.3454   |
  | 3.9283        | 2.0   | 2418 | 3.1443          | 16.3537 | 7.9374 | 15.8565 | 15.7281   |
  | 3.5985        | 3.0   | 3627 | 3.1004          | 17.9042 | 9.1908 | 17.5268 | 17.385    |
  | 3.4285        | 4.0   | 4836 | 3.0578          | 16.3118 | 8.4563 | 15.9252 | 15.9109   |
  | 3.3222        | 5.0   | 6045 | 3.0587          | 17.5106 | 8.6579 | 17.2096 | 17.1079   |
  | 3.2554        | 6.0   | 7254 | 3.0497          | 16.9153 | 8.0973 | 16.5874 | 16.4807   |
  | 3.2085        | 7.0   | 8463 | 3.0309          | 16.3789 | 7.9306 | 16.1233 | 16.0097   |
  | 3.1856        | 8.0   | 9672 | 3.0329          | 16.3034 | 7.8192 | 16.0316 | 15.9173   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  