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 was created by following the [huggingface tutorial](https://huggingface.co/course/chapter7/5?fw=pt).
  
  It achieves the following results on the evaluation set:
  - Loss: 3.0173
  - Rouge1: 16.7977
  - Rouge2: 8.6849
  - Rougel: 16.4822
  - Rougelsum: 16.4975
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 3.4693        | 1.0   | 1209 | 3.1215          | 17.5363 | 8.3875 | 17.0229 | 16.9653   |
  | 3.4231        | 2.0   | 2418 | 3.0474          | 16.7927 | 8.3533 | 16.2748 | 16.2379   |
  | 3.271         | 3.0   | 3627 | 3.0440          | 16.7233 | 7.9129 | 16.2385 | 16.1915   |
  | 3.1885        | 4.0   | 4836 | 3.0264          | 16.3078 | 7.5751 | 15.844  | 15.889    |
  | 3.1216        | 5.0   | 6045 | 3.0277          | 17.259  | 8.7504 | 16.8293 | 16.8543   |
  | 3.0739        | 6.0   | 7254 | 3.0188          | 16.8374 | 8.6457 | 16.4407 | 16.4743   |
  | 3.0393        | 7.0   | 8463 | 3.0161          | 17.3064 | 8.7822 | 16.9423 | 16.9543   |
  | 3.0202        | 8.0   | 9672 | 3.0173          | 16.7977 | 8.6849 | 16.4822 | 16.4975   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  