readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-cnn-dailymail
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: summarization
      dataset:
        name: cnn_dailymail
        type: cnn_dailymail
        config: 3.0.0
        split: train
        args: 3.0.0
      metrics:
      - name: Rouge1
        type: rouge
        value: 32.8352
  ---
  
  <!-- 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-cnn-dailymail
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the cnn_dailymail dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7294
  - Rouge1: 32.8352
  - Rouge2: 17.0633
  - Rougel: 29.0888
  - Rougelsum: 30.8226
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | No log        | 1.0   | 8973  | 1.9272          | 31.6634 | 16.1653 | 28.1624 | 29.7819   |
  | No log        | 2.0   | 17946 | 1.8282          | 32.1032 | 16.4388 | 28.4914 | 30.1856   |
  | No log        | 3.0   | 26919 | 1.7967          | 32.5721 | 16.8392 | 28.8483 | 30.5764   |
  | 2.1615        | 4.0   | 35892 | 1.7640          | 32.6788 | 16.94   | 28.994  | 30.6883   |
  | 2.1615        | 5.0   | 44865 | 1.7450          | 32.8129 | 17.048  | 29.0788 | 30.8106   |
  | 2.1615        | 6.0   | 53838 | 1.7379          | 32.7074 | 16.9641 | 28.9745 | 30.7043   |
  | 2.1615        | 7.0   | 62811 | 1.7317          | 32.7692 | 17.0116 | 29.0395 | 30.7685   |
  | 2.0886        | 8.0   | 71784 | 1.7294          | 32.8352 | 17.0633 | 29.0888 | 30.8226   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  