readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-english-100
    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-100
  
  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: 6.6225
  - Rouge1: 3.909
  - Rouge2: 0.9312
  - Rougel: 3.3835
  - Rougelsum: 3.7786
  
  ## 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        | 0.96  | 12   | 14.4949         | 2.7398 | 0.7181 | 2.491  | 2.6561    |
  | No log        | 1.96  | 24   | 10.5056         | 4.4428 | 1.4293 | 3.8469 | 4.2869    |
  | No log        | 2.96  | 36   | 8.9856          | 4.1179 | 1.229  | 3.5726 | 3.9693    |
  | No log        | 3.96  | 48   | 7.7950          | 3.9217 | 1.1339 | 3.4256 | 3.7905    |
  | No log        | 4.96  | 60   | 7.0734          | 3.8004 | 1.0326 | 3.3246 | 3.6766    |
  | No log        | 5.96  | 72   | 6.7897          | 3.6351 | 0.9162 | 3.1839 | 3.5149    |
  | No log        | 6.96  | 84   | 6.6610          | 3.7486 | 0.8829 | 3.2583 | 3.6193    |
  | No log        | 7.96  | 96   | 6.6225          | 3.909  | 0.9312 | 3.3835 | 3.7786    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  