readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-summarizer-finetuned
    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-summarizer-finetuned
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.0158
  - Rouge1: 17.7167
  - Rouge2: 8.7443
  - Rougel: 17.4487
  - Rougelsum: 17.4013
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.8514        | 1.0   | 1209 | 3.2992          | 14.7682 | 6.17   | 14.2741 | 14.2171   |
  | 3.8706        | 2.0   | 2418 | 3.1206          | 16.1753 | 7.7142 | 15.436  | 15.5325   |
  | 3.5426        | 3.0   | 3627 | 3.0748          | 17.9388 | 8.786  | 17.3878 | 17.3805   |
  | 3.3773        | 4.0   | 4836 | 3.0461          | 16.79   | 7.9251 | 16.4337 | 16.3482   |
  | 3.2734        | 5.0   | 6045 | 3.0438          | 17.201  | 8.2405 | 16.9939 | 16.9181   |
  | 3.194         | 6.0   | 7254 | 3.0227          | 17.3508 | 8.4746 | 17.0519 | 17.0831   |
  | 3.1556        | 7.0   | 8463 | 3.0201          | 17.6119 | 8.686  | 17.3536 | 17.3228   |
  | 3.1256        | 8.0   | 9672 | 3.0158          | 17.7167 | 8.7443 | 17.4487 | 17.4013   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  