readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - xlsum
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-xlsum-10-epoch
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: xlsum
        type: xlsum
        args: english
      metrics:
      - name: Rouge1
        type: rouge
        value: 31.6534
  ---
  
  <!-- 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. -->
  
  # t5-small-finetuned-xlsum-10-epoch
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.2204
  - Rouge1: 31.6534
  - Rouge2: 10.0563
  - Rougel: 24.8104
  - Rougelsum: 24.8732
  - Gen Len: 18.7913
  
  ## 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: 2e-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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.6512        | 1.0   | 19158  | 2.3745          | 29.756  | 8.4006  | 22.9753 | 23.0287   | 18.8245 |
  | 2.6012        | 2.0   | 38316  | 2.3183          | 30.5327 | 9.0206  | 23.7263 | 23.7805   | 18.813  |
  | 2.5679        | 3.0   | 57474  | 2.2853          | 30.9771 | 9.4156  | 24.1555 | 24.2127   | 18.7905 |
  | 2.5371        | 4.0   | 76632  | 2.2660          | 31.0578 | 9.5592  | 24.2983 | 24.3587   | 18.7941 |
  | 2.5133        | 5.0   | 95790  | 2.2498          | 31.3756 | 9.7889  | 24.5317 | 24.5922   | 18.7971 |
  | 2.4795        | 6.0   | 114948 | 2.2378          | 31.4961 | 9.8935  | 24.6648 | 24.7218   | 18.7929 |
  | 2.4967        | 7.0   | 134106 | 2.2307          | 31.44   | 9.9125  | 24.6298 | 24.6824   | 18.8221 |
  | 2.4678        | 8.0   | 153264 | 2.2250          | 31.5875 | 10.004  | 24.7581 | 24.8125   | 18.7809 |
  | 2.46          | 9.0   | 172422 | 2.2217          | 31.6413 | 10.0311 | 24.8063 | 24.8641   | 18.7951 |
  | 2.4494        | 10.0  | 191580 | 2.2204          | 31.6534 | 10.0563 | 24.8104 | 24.8732   | 18.7913 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.13.1+cpu
  - Datasets 2.8.0
  - Tokenizers 0.10.3
  