readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-test-amazon-v2
    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-test-amazon-v2
  
  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: 2.0555
  - Rouge1: 27.8124
  - Rouge2: 15.3682
  - Rougel: 27.8646
  - Rougelsum: 27.9044
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 6.2982        | 1.0   | 1935  | 2.7890          | 23.293  | 12.7229 | 23.3183 | 23.3368   |
  | 2.9801        | 2.0   | 3870  | 2.4341          | 25.9888 | 14.0833 | 26.07   | 26.0897   |
  | 2.5025        | 3.0   | 5805  | 2.2611          | 26.5127 | 14.5775 | 26.5105 | 26.5442   |
  | 2.2681        | 4.0   | 7740  | 2.1966          | 27.7476 | 14.9971 | 27.835  | 27.8186   |
  | 2.1198        | 5.0   | 9675  | 2.1209          | 27.3796 | 15.1938 | 27.4549 | 27.4759   |
  | 2.0089        | 6.0   | 11610 | 2.0856          | 27.6637 | 15.2345 | 27.7419 | 27.7608   |
  | 1.9416        | 7.0   | 13545 | 2.0637          | 27.9013 | 15.3682 | 27.9621 | 27.9833   |
  | 1.9034        | 8.0   | 15480 | 2.0555          | 27.8124 | 15.3682 | 27.8646 | 27.9044   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  