readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - eli5
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-eli5-extra-finetune
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: eli5
        type: eli5
        config: LFQA_reddit
        split: train_eli5
        args: LFQA_reddit
      metrics:
      - name: Rouge1
        type: rouge
        value: 9.8647
  ---
  
  <!-- 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-eli5-extra-finetune
  
  This model is a fine-tuned version of [Sandipan1994/t5-small-finetuned-eli5](https://huggingface.co/Sandipan1994/t5-small-finetuned-eli5) on the eli5 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.6711
  - Rouge1: 9.8647
  - Rouge2: 1.9166
  - Rougel: 7.9523
  - Rougelsum: 9.1657
  - Gen Len: 18.9981
  
  ## 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: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | 3.8865        | 1.0   | 17040 | 3.6929          | 9.9257 | 1.9075 | 8.026  | 9.2238    | 19.0    |
  | 3.8777        | 2.0   | 34080 | 3.6764          | 9.8568 | 1.9027 | 7.9443 | 9.1535    | 18.9981 |
  | 3.8667        | 3.0   | 51120 | 3.6711          | 9.8647 | 1.9166 | 7.9523 | 9.1657    | 18.9981 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  