readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wikihow
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-wikihow_3epoch_b8_lr3e-3
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: wikihow
        type: wikihow
        args: all
      metrics:
      - name: Rouge1
        type: rouge
        value: 27.1711
  ---
  
  <!-- 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-3
  
  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: 2.3163
  - Rouge1: 27.1711
  - Rouge2: 10.6296
  - Rougel: 23.206
  - Rougelsum: 26.4801
  - Gen Len: 18.5433
  
  ## 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: 0.003
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 3.0734        | 0.25  | 5000  | 2.7884          | 22.4825 | 7.2492  | 19.243  | 21.9167   | 18.0616 |
  | 2.9201        | 0.51  | 10000 | 2.7089          | 24.0869 | 8.0348  | 20.4814 | 23.4541   | 18.5994 |
  | 2.8403        | 0.76  | 15000 | 2.6390          | 24.62   | 8.3776  | 20.8736 | 23.9784   | 18.4676 |
  | 2.7764        | 1.02  | 20000 | 2.5943          | 24.1504 | 8.3933  | 20.8271 | 23.5382   | 18.4078 |
  | 2.6641        | 1.27  | 25000 | 2.5428          | 25.6574 | 9.2371  | 21.8576 | 24.9558   | 18.4249 |
  | 2.6369        | 1.53  | 30000 | 2.5042          | 25.5208 | 9.254   | 21.6673 | 24.8589   | 18.6467 |
  | 2.6           | 1.78  | 35000 | 2.4637          | 26.094  | 9.7003  | 22.3097 | 25.4695   | 18.5065 |
  | 2.5562        | 2.03  | 40000 | 2.4285          | 26.5374 | 9.9222  | 22.5291 | 25.8836   | 18.5553 |
  | 2.4322        | 2.29  | 45000 | 2.3858          | 26.939  | 10.3555 | 23.0211 | 26.2834   | 18.5614 |
  | 2.4106        | 2.54  | 50000 | 2.3537          | 26.7423 | 10.2816 | 22.7986 | 26.083    | 18.5792 |
  | 2.3731        | 2.8   | 55000 | 2.3163          | 27.1711 | 10.6296 | 23.206  | 26.4801   | 18.5433 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  