readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wikihow
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-wikihow_3epoch_b8_lr3e-4
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: wikihow
        type: wikihow
        args: all
      metrics:
      - name: Rouge1
        type: rouge
        value: 27.3718
  ---
  
  <!-- 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-wikihow_3epoch_b8_lr3e-4
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikihow dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3136
  - Rouge1: 27.3718
  - Rouge2: 10.6235
  - Rougel: 23.3396
  - Rougelsum: 26.6889
  - Gen Len: 18.5194
  
  ## 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: 0.0003
  - 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: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.8029        | 0.25  | 5000  | 2.5368          | 25.2267 | 8.9048  | 21.2588 | 24.5804   | 18.4303 |
  | 2.6924        | 0.51  | 10000 | 2.4725          | 25.6553 | 9.1904  | 21.7633 | 24.9807   | 18.5549 |
  | 2.6369        | 0.76  | 15000 | 2.4332          | 26.2895 | 9.7203  | 22.3286 | 25.6009   | 18.4185 |
  | 2.5994        | 1.02  | 20000 | 2.4051          | 26.1779 | 9.5708  | 22.3531 | 25.5357   | 18.561  |
  | 2.521         | 1.27  | 25000 | 2.3805          | 26.7558 | 10.0411 | 22.7252 | 26.0476   | 18.304  |
  | 2.5091        | 1.53  | 30000 | 2.3625          | 26.6439 | 10.0698 | 22.6662 | 25.9537   | 18.5437 |
  | 2.4941        | 1.78  | 35000 | 2.3498          | 26.9322 | 10.2817 | 23.0002 | 26.2604   | 18.4953 |
  | 2.4848        | 2.03  | 40000 | 2.3424          | 27.0381 | 10.3452 | 22.9749 | 26.3407   | 18.5749 |
  | 2.4268        | 2.29  | 45000 | 2.3272          | 27.2386 | 10.4595 | 23.1866 | 26.5541   | 18.4954 |
  | 2.4263        | 2.54  | 50000 | 2.3226          | 27.1489 | 10.532  | 23.1428 | 26.4657   | 18.5583 |
  | 2.4161        | 2.8   | 55000 | 2.3136          | 27.3718 | 10.6235 | 23.3396 | 26.6889   | 18.5194 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  