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: 3.1185
  - Rouge1: 17.2081
  - Rouge2: 8.8374
  - Rougel: 16.8033
  - Rougelsum: 16.663
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | No log        | 1.0   | 303  | 3.9821          | 8.3993  | 2.0894 | 8.1427  | 8.135     |
  | No log        | 2.0   | 606  | 3.3511          | 13.1381 | 5.7193 | 12.8494 | 12.8375   |
  | No log        | 3.0   | 909  | 3.2235          | 15.2502 | 6.5903 | 14.728  | 14.612    |
  | 5.8943        | 4.0   | 1212 | 3.1695          | 16.1725 | 8.1638 | 15.7655 | 15.6068   |
  | 5.8943        | 5.0   | 1515 | 3.1579          | 16.3126 | 7.9727 | 15.8308 | 15.7236   |
  | 5.8943        | 6.0   | 1818 | 3.1346          | 16.8323 | 8.088  | 16.3863 | 16.3343   |
  | 5.8943        | 7.0   | 2121 | 3.1181          | 16.965  | 8.5799 | 16.6418 | 16.5064   |
  | 3.7097        | 8.0   | 2424 | 3.1185          | 17.2081 | 8.8374 | 16.8033 | 16.663    |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  