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: 3.0270
  - Rouge1: 16.9866
  - Rouge2: 8.4614
  - Rougel: 16.484
  - Rougelsum: 16.6388
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.9791        | 1.0   | 1209 | 3.3127          | 13.2057 | 5.6236 | 12.856  | 12.9369   |
  | 3.9087        | 2.0   | 2418 | 3.1392          | 16.5366 | 7.8474 | 15.7781 | 15.7997   |
  | 3.588         | 3.0   | 3627 | 3.0870          | 17.6214 | 8.8031 | 17.0347 | 17.1196   |
  | 3.4143        | 4.0   | 4836 | 3.0525          | 16.5647 | 8.2045 | 15.967  | 16.0259   |
  | 3.3263        | 5.0   | 6045 | 3.0600          | 16.7381 | 7.8033 | 16.1291 | 16.1999   |
  | 3.2487        | 6.0   | 7254 | 3.0288          | 16.8767 | 8.5432 | 16.4201 | 16.5014   |
  | 3.2112        | 7.0   | 8463 | 3.0318          | 17.125  | 8.3547 | 16.5445 | 16.6221   |
  | 3.1817        | 8.0   | 9672 | 3.0270          | 16.9866 | 8.4614 | 16.484  | 16.6388   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  