readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - xsum
  metrics:
  - rouge
  model-index:
  - name: t5_finetuned_xsum_hr
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: xsum
        type: xsum
        config: default
        split: train
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 29.1239
  ---
  
  <!-- 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_finetuned_xsum_hr
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.4224
  - Rouge1: 29.1239
  - Rouge2: 8.3165
  - Rougel: 22.9946
  - Rougelsum: 22.9996
  - Gen Len: 18.819
  
  ## 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: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.6839        | 1.0   | 12753 | 2.4474          | 28.721  | 8.0397 | 22.6568 | 22.6527   | 18.8324 |
  | 2.6425        | 2.0   | 25506 | 2.4224          | 29.1239 | 8.3165 | 22.9946 | 22.9996   | 18.819  |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  