readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-amazon-pr-zhsum
    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-finetuned-amazon-pr-zhsum
  
  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: 1.1751
  - Rouge1: 0.1109
  - Rouge2: 0.0318
  - Rougel: 0.1109
  - Rougelsum: 0.1115
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 6.0524        | 1.0   | 381  | 1.5214          | 0.0997 | 0.0281 | 0.0991 | 0.1001    |
  | 2.0421        | 2.0   | 762  | 1.4323          | 0.1085 | 0.0287 | 0.1087 | 0.1090    |
  | 1.6931        | 3.0   | 1143 | 1.3138          | 0.1118 | 0.0292 | 0.1118 | 0.1123    |
  | 1.5288        | 4.0   | 1524 | 1.2603          | 0.1102 | 0.0314 | 0.1101 | 0.1105    |
  | 1.4346        | 5.0   | 1905 | 1.2373          | 0.1096 | 0.0297 | 0.1094 | 0.1099    |
  | 1.3827        | 6.0   | 2286 | 1.1859          | 0.1101 | 0.0305 | 0.1099 | 0.1105    |
  | 1.3167        | 7.0   | 2667 | 1.1778          | 0.1104 | 0.0311 | 0.1104 | 0.1109    |
  | 1.3248        | 8.0   | 3048 | 1.1751          | 0.1109 | 0.0318 | 0.1109 | 0.1115    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  