readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - cc_news_es_titles
  model-index:
  - name: encoder_decoder_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. -->
  
  # encoder_decoder_es
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the cc_news_es_titles dataset.
  It achieves the following results on the evaluation set:
  - Loss: 7.8773
  - Rouge2 Precision: 0.002
  - Rouge2 Recall: 0.0116
  - Rouge2 Fmeasure: 0.0034
  
  ## 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: 0.003
  - train_batch_size: 32
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 7.8807        | 1.0   | 5784  | 7.8976          | 0.0023           | 0.012         | 0.0038          |
  | 7.8771        | 2.0   | 11568 | 7.8873          | 0.0018           | 0.0099        | 0.003           |
  | 7.8588        | 3.0   | 17352 | 7.8819          | 0.0015           | 0.0085        | 0.0025          |
  | 7.8507        | 4.0   | 23136 | 7.8773          | 0.002            | 0.0116        | 0.0034          |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.1
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  