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: 3.0294
  - Rouge1: 16.4846
  - Rouge2: 7.8849
  - Rougel: 16.2726
  - Rougelsum: 16.2173
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.5928        | 1.0   | 1209 | 3.3005          | 14.7927 | 6.4642 | 14.3032 | 14.2436   |
  | 3.9024        | 2.0   | 2418 | 3.1399          | 16.8294 | 8.5707 | 16.1439 | 16.133    |
  | 3.5806        | 3.0   | 3627 | 3.0869          | 18.1262 | 9.1916 | 17.7121 | 17.7184   |
  | 3.4201        | 4.0   | 4836 | 3.0590          | 17.6134 | 8.915  | 17.209  | 17.1519   |
  | 3.3202        | 5.0   | 6045 | 3.0598          | 17.6322 | 8.5392 | 17.4438 | 17.3057   |
  | 3.2436        | 6.0   | 7254 | 3.0409          | 16.7409 | 8.107  | 16.5385 | 16.496    |
  | 3.2079        | 7.0   | 8463 | 3.0332          | 16.722  | 8.0183 | 16.4492 | 16.4297   |
  | 3.1801        | 8.0   | 9672 | 3.0294          | 16.4846 | 7.8849 | 16.2726 | 16.2173   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  