readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - mlsum
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-mlsum
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: mlsum
        type: mlsum
        args: es
      metrics:
      - name: Rouge1
        type: rouge
        value: 1.1475
  ---
  
  <!-- 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-mlsum
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the mlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: nan
  - Rouge1: 1.1475
  - Rouge2: 0.1284
  - Rougel: 1.0634
  - Rougelsum: 1.0778
  - Gen Len: 3.7939
  
  ## 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: 2e-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: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | nan           | 1.0   | 808  | nan             | 1.1475 | 0.1284 | 1.0634 | 1.0778    | 3.7939  |
  
  
  ### Framework versions
  
  - Transformers 4.10.3
  - Pytorch 1.9.0+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  