readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-portuguese
    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-portuguese
  
  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: 2.0428
  - Rouge1: 9.4966
  - Rouge2: 4.2224
  - Rougel: 7.9845
  - Rougelsum: 8.8641
  
  ## 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   | 334  | 2.2258          | 7.3686 | 2.9066 | 6.3167 | 6.8758    |
  | No log        | 2.0   | 668  | 2.1389          | 9.0551 | 3.8395 | 7.6578 | 8.4641    |
  | No log        | 3.0   | 1002 | 2.1030          | 9.2792 | 3.9352 | 7.8259 | 8.663     |
  | No log        | 4.0   | 1336 | 2.0841          | 9.337  | 4.0647 | 7.8662 | 8.693     |
  | 3.2831        | 5.0   | 1670 | 2.0487          | 9.4244 | 4.0821 | 7.8633 | 8.7111    |
  | 3.2831        | 6.0   | 2004 | 2.0580          | 9.4598 | 4.1598 | 7.9511 | 8.8299    |
  | 3.2831        | 7.0   | 2338 | 2.0426          | 9.501  | 4.1885 | 7.9803 | 8.8612    |
  | 3.2831        | 8.0   | 2672 | 2.0428          | 9.4966 | 4.2224 | 7.9845 | 8.8641    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  