readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - mlsum
  metrics:
  - rouge
  model-index:
  - name: mt5-small-test-ged-mlsum_max_target_length_10
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: mlsum
        type: mlsum
        args: es
      metrics:
      - name: Rouge1
        type: rouge
        value: 74.8229
  ---
  
  <!-- 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-test-ged-mlsum_max_target_length_10
  
  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: 0.3341
  - Rouge1: 74.8229
  - Rouge2: 68.1808
  - Rougel: 74.8297
  - Rougelsum: 74.8414
  
  ## 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 |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 0.5565        | 1.0   | 33296  | 0.3827          | 69.9041 | 62.821  | 69.8709 | 69.8924   |
  | 0.2636        | 2.0   | 66592  | 0.3552          | 72.0701 | 65.4937 | 72.0787 | 72.091    |
  | 0.2309        | 3.0   | 99888  | 0.3525          | 72.5071 | 65.8026 | 72.5132 | 72.512    |
  | 0.2109        | 4.0   | 133184 | 0.3346          | 74.0842 | 67.4776 | 74.0887 | 74.0968   |
  | 0.1972        | 5.0   | 166480 | 0.3398          | 74.6051 | 68.6024 | 74.6177 | 74.6365   |
  | 0.1867        | 6.0   | 199776 | 0.3283          | 74.9022 | 68.2146 | 74.9023 | 74.926    |
  | 0.1785        | 7.0   | 233072 | 0.3325          | 74.8631 | 68.2468 | 74.8843 | 74.9026   |
  | 0.1725        | 8.0   | 266368 | 0.3341          | 74.8229 | 68.1808 | 74.8297 | 74.8414   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  