readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - xlsum
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-tradition-zh
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: xlsum
        type: xlsum
        args: chinese_traditional
      metrics:
      - name: Rouge1
        type: rouge
        value: 5.7806
  ---
  
  <!-- 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-tradition-zh
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.9218
  - Rouge1: 5.7806
  - Rouge2: 1.266
  - Rougel: 5.761
  - Rougelsum: 5.7833
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 4.542         | 1.0   | 2336  | 3.1979          | 4.8334 | 1.025  | 4.8142 | 4.8326    |
  | 3.7542        | 2.0   | 4672  | 3.0662          | 5.2155 | 1.0978 | 5.2025 | 5.2158    |
  | 3.5706        | 3.0   | 7008  | 3.0070          | 5.5471 | 1.3397 | 5.5386 | 5.5391    |
  | 3.4668        | 4.0   | 9344  | 2.9537          | 5.5865 | 1.1558 | 5.5816 | 5.5964    |
  | 3.4082        | 5.0   | 11680 | 2.9391          | 5.8061 | 1.3462 | 5.7944 | 5.812     |
  | 3.375         | 6.0   | 14016 | 2.9218          | 5.7806 | 1.266  | 5.761  | 5.7833    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  