readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-wikinewssum-test
    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-small-wikinewssum-test
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.9354
  - Rouge1: 6.8433
  - Rouge2: 2.5498
  - Rougel: 5.6114
  - Rougelsum: 6.353
  
  ## 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: 12
  - eval_batch_size: 12
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | No log        | 1.0   | 661  | 3.2810          | 6.4161 | 2.403  | 5.3674 | 6.0329    |
  | No log        | 2.0   | 1322 | 3.1515          | 6.9291 | 2.6826 | 5.6839 | 6.4359    |
  | No log        | 3.0   | 1983 | 3.0565          | 6.7939 | 2.6113 | 5.6133 | 6.3126    |
  | No log        | 4.0   | 2644 | 2.9815          | 6.0279 | 2.1637 | 4.9892 | 5.5962    |
  | No log        | 5.0   | 3305 | 2.9645          | 6.3926 | 2.339  | 5.2716 | 5.9443    |
  | 3.9937        | 6.0   | 3966 | 2.9476          | 6.4739 | 2.3615 | 5.3473 | 6.0089    |
  | 3.9937        | 7.0   | 4627 | 2.9405          | 6.615  | 2.4309 | 5.4493 | 6.1445    |
  | 3.9937        | 8.0   | 5288 | 2.9354          | 6.8433 | 2.5498 | 5.6114 | 6.353     |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  