readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-german
    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-german
  
  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: 2.5135
  - Rouge1: 8.0553
  - Rouge2: 2.7846
  - Rougel: 6.2182
  - Rougelsum: 7.6203
  
  ## 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   | 723  | 2.7112          | 7.3681 | 2.3679 | 5.5705 | 6.7588    |
  | No log        | 2.0   | 1446 | 2.6178          | 7.8539 | 2.7551 | 6.2081 | 7.4139    |
  | No log        | 3.0   | 2169 | 2.5756          | 7.8401 | 2.6075 | 6.0135 | 7.4303    |
  | No log        | 4.0   | 2892 | 2.5465          | 8.1097 | 2.8525 | 6.268  | 7.6482    |
  | 3.4589        | 5.0   | 3615 | 2.5315          | 8.0192 | 2.7848 | 6.2484 | 7.5859    |
  | 3.4589        | 6.0   | 4338 | 2.5222          | 8.1063 | 2.8986 | 6.337  | 7.6564    |
  | 3.4589        | 7.0   | 5061 | 2.5136          | 8.0565 | 2.8707 | 6.2732 | 7.6105    |
  | 3.4589        | 8.0   | 5784 | 2.5135          | 8.0553 | 2.7846 | 6.2182 | 7.6203    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  