readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wikihow
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-wikihow_3epoch_b8_lr3e-5
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: wikihow
        type: wikihow
        args: all
      metrics:
      - name: Rouge1
        type: rouge
        value: 25.9411
  ---
  
  <!-- 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-5
  
  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: 2.4836
  - Rouge1: 25.9411
  - Rouge2: 9.226
  - Rougel: 21.9087
  - Rougelsum: 25.2863
  - Gen Len: 18.4076
  
  ## 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: 3e-05
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.912         | 0.25  | 5000  | 2.6285          | 23.6659 | 7.8535 | 19.9837 | 22.9884   | 18.3867 |
  | 2.8115        | 0.51  | 10000 | 2.5820          | 24.7979 | 8.4888 | 20.8719 | 24.1321   | 18.3292 |
  | 2.767         | 0.76  | 15000 | 2.5555          | 25.0857 | 8.6437 | 21.149  | 24.4256   | 18.2981 |
  | 2.742         | 1.02  | 20000 | 2.5330          | 25.3431 | 8.8393 | 21.425  | 24.7032   | 18.3749 |
  | 2.7092        | 1.27  | 25000 | 2.5203          | 25.5338 | 8.9281 | 21.5378 | 24.9045   | 18.3399 |
  | 2.6989        | 1.53  | 30000 | 2.5065          | 25.4792 | 8.9745 | 21.4941 | 24.8458   | 18.4565 |
  | 2.6894        | 1.78  | 35000 | 2.5018          | 25.6815 | 9.1218 | 21.6958 | 25.0557   | 18.406  |
  | 2.6897        | 2.03  | 40000 | 2.4944          | 25.8241 | 9.2127 | 21.8205 | 25.1801   | 18.4228 |
  | 2.6664        | 2.29  | 45000 | 2.4891          | 25.8241 | 9.1662 | 21.7807 | 25.1615   | 18.4258 |
  | 2.6677        | 2.54  | 50000 | 2.4855          | 25.7435 | 9.145  | 21.765  | 25.0858   | 18.4329 |
  | 2.6631        | 2.8   | 55000 | 2.4836          | 25.9411 | 9.226  | 21.9087 | 25.2863   | 18.4076 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  