readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-english
    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-english
  
  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: 2.3040
  - Rouge1: 8.9565
  - Rouge2: 3.6563
  - Rougel: 7.1346
  - Rougelsum: 8.3802
  
  ## 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   | 1010 | 2.4360          | 8.7287 | 3.5817 | 7.0093 | 8.1879    |
  | No log        | 2.0   | 2020 | 2.3922          | 8.7227 | 3.5385 | 6.96   | 8.1887    |
  | No log        | 3.0   | 3030 | 2.3422          | 8.8565 | 3.5772 | 7.0203 | 8.2957    |
  | No log        | 4.0   | 4040 | 2.3288          | 8.89   | 3.645  | 7.0602 | 8.3314    |
  | 3.1253        | 5.0   | 5050 | 2.3209          | 8.868  | 3.6109 | 7.0537 | 8.299     |
  | 3.1253        | 6.0   | 6060 | 2.3127          | 8.9488 | 3.6615 | 7.1044 | 8.3785    |
  | 3.1253        | 7.0   | 7070 | 2.3056          | 8.9366 | 3.6507 | 7.1338 | 8.3615    |
  | 3.1253        | 8.0   | 8080 | 2.3040          | 8.9565 | 3.6563 | 7.1346 | 8.3802    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  