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: 16.6807
  - Rouge2: 8.0004
  - Rougel: 16.2251
  - Rougelsum: 16.1743
  
  ## 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          | 14.7863 | 6.5038 | 14.3031 | 14.2522   |
  | 3.9024        | 2.0   | 2418 | 3.1399          | 16.9257 | 8.6583 | 16.15   | 16.1299   |
  | 3.5806        | 3.0   | 3627 | 3.0869          | 18.2734 | 9.1667 | 17.7441 | 17.5782   |
  | 3.4201        | 4.0   | 4836 | 3.0590          | 17.763  | 8.9447 | 17.1833 | 17.1661   |
  | 3.3202        | 5.0   | 6045 | 3.0598          | 17.7754 | 8.5695 | 17.4139 | 17.2653   |
  | 3.2436        | 6.0   | 7254 | 3.0409          | 16.8423 | 8.1593 | 16.5392 | 16.4297   |
  | 3.2079        | 7.0   | 8463 | 3.0332          | 16.8991 | 8.1574 | 16.4229 | 16.3515   |
  | 3.1801        | 8.0   | 9672 | 3.0294          | 16.6807 | 8.0004 | 16.2251 | 16.1743   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  