readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-all-languages
    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-all-languages
  
  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: 2.2454
  - Rouge1: 8.3826
  - Rouge2: 3.5524
  - Rougel: 6.8656
  - Rougelsum: 7.8362
  
  ## 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   | 3467  | 2.4034          | 8.0363 | 3.2484 | 6.5409 | 7.477     |
  | No log        | 2.0   | 6934  | 2.3276          | 8.1054 | 3.2905 | 6.5765 | 7.5687    |
  | No log        | 3.0   | 10401 | 2.2976          | 8.169  | 3.4272 | 6.6597 | 7.6435    |
  | No log        | 4.0   | 13868 | 2.2795          | 8.2941 | 3.5353 | 6.7881 | 7.7664    |
  | 2.8057        | 5.0   | 17335 | 2.2621          | 8.3302 | 3.5599 | 6.8238 | 7.7928    |
  | 2.8057        | 6.0   | 20802 | 2.2547          | 8.3818 | 3.5886 | 6.8672 | 7.844     |
  | 2.8057        | 7.0   | 24269 | 2.2472          | 8.3809 | 3.5696 | 6.8575 | 7.8327    |
  | 2.8057        | 8.0   | 27736 | 2.2454          | 8.3826 | 3.5524 | 6.8656 | 7.8362    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  