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: 3.0282
  - Rouge1: 17.629
  - Rouge2: 8.5256
  - Rougel: 17.1329
  - Rougelsum: 17.1403
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 6.6665        | 1.0   | 1209 | 3.2917          | 13.9446 | 5.4878  | 13.3696 | 13.3884   |
  | 3.9091        | 2.0   | 2418 | 3.1575          | 16.5515 | 8.4045  | 15.734  | 15.8858   |
  | 3.5987        | 3.0   | 3627 | 3.0803          | 18.4586 | 10.0134 | 17.6448 | 17.8592   |
  | 3.4269        | 4.0   | 4836 | 3.0492          | 17.9493 | 8.9283  | 17.0803 | 17.1683   |
  | 3.3213        | 5.0   | 6045 | 3.0466          | 18.124  | 8.967   | 17.4472 | 17.4445   |
  | 3.2368        | 6.0   | 7254 | 3.0405          | 17.5527 | 8.4814  | 16.9722 | 17.0104   |
  | 3.2039        | 7.0   | 8463 | 3.0335          | 17.5116 | 8.2969  | 17.006  | 17.0084   |
  | 3.1834        | 8.0   | 9672 | 3.0282          | 17.629  | 8.5256  | 17.1329 | 17.1403   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  