readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-spanish
    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-base-wikinewssum-spanish
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.2394
  - Rouge1: 7.9732
  - Rouge2: 3.5041
  - Rougel: 6.6713
  - Rougelsum: 7.5229
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - 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   | 528  | 2.3707          | 6.687  | 2.9169 | 5.6793 | 6.2978    |
  | No log        | 2.0   | 1056 | 2.3140          | 7.9518 | 3.4529 | 6.7265 | 7.4984    |
  | No log        | 3.0   | 1584 | 2.2848          | 7.9708 | 3.5344 | 6.7272 | 7.534     |
  | No log        | 4.0   | 2112 | 2.2668          | 8.0252 | 3.5323 | 6.7319 | 7.5819    |
  | 3.2944        | 5.0   | 2640 | 2.2532          | 8.0143 | 3.534  | 6.7155 | 7.582     |
  | 3.2944        | 6.0   | 3168 | 2.2399          | 7.9525 | 3.4849 | 6.6716 | 7.5155    |
  | 3.2944        | 7.0   | 3696 | 2.2376          | 7.9405 | 3.4661 | 6.6559 | 7.5043    |
  | 3.2944        | 8.0   | 4224 | 2.2394          | 7.9732 | 3.5041 | 6.6713 | 7.5229    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  