readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-xsum
    results: []
  ---
  
  <!-- 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-xsum
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2715
  - Rouge1: 0.8783
  - Rouge2: 0.8348
  - Rougel: 0.8739
  - Rougelsum: 0.8746
  
  ## 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | No log        | 1.0   | 21   | 0.6229          | 0.7109 | 0.6524 | 0.7061 | 0.7071    |
  | No log        | 2.0   | 42   | 0.4551          | 0.7062 | 0.6477 | 0.7008 | 0.7017    |
  | No log        | 3.0   | 63   | 0.3653          | 0.7854 | 0.7293 | 0.7818 | 0.7823    |
  | No log        | 4.0   | 84   | 0.3170          | 0.8117 | 0.7606 | 0.8076 | 0.8101    |
  | No log        | 5.0   | 105  | 0.3047          | 0.8384 | 0.7893 | 0.8346 | 0.834     |
  | No log        | 6.0   | 126  | 0.2916          | 0.8489 | 0.8022 | 0.8454 | 0.8454    |
  | No log        | 7.0   | 147  | 0.2852          | 0.8512 | 0.8085 | 0.8479 | 0.8478    |
  | No log        | 8.0   | 168  | 0.2778          | 0.869  | 0.8249 | 0.8645 | 0.8651    |
  | No log        | 9.0   | 189  | 0.2762          | 0.8702 | 0.8258 | 0.8657 | 0.8663    |
  | No log        | 10.0  | 210  | 0.2760          | 0.8734 | 0.8294 | 0.8681 | 0.8693    |
  | No log        | 11.0  | 231  | 0.2749          | 0.8734 | 0.8294 | 0.8681 | 0.8693    |
  | No log        | 12.0  | 252  | 0.2747          | 0.8739 | 0.8303 | 0.8688 | 0.8699    |
  | No log        | 13.0  | 273  | 0.2743          | 0.8735 | 0.8295 | 0.8681 | 0.8694    |
  | No log        | 14.0  | 294  | 0.2747          | 0.8773 | 0.8335 | 0.8726 | 0.8731    |
  | No log        | 15.0  | 315  | 0.2748          | 0.8773 | 0.8335 | 0.8726 | 0.8731    |
  | No log        | 16.0  | 336  | 0.2734          | 0.8779 | 0.8344 | 0.8734 | 0.874     |
  | No log        | 17.0  | 357  | 0.2733          | 0.8779 | 0.8343 | 0.8733 | 0.8739    |
  | No log        | 18.0  | 378  | 0.2729          | 0.8779 | 0.8344 | 0.8734 | 0.874     |
  | No log        | 19.0  | 399  | 0.2718          | 0.8793 | 0.8357 | 0.8745 | 0.875     |
  | No log        | 20.0  | 420  | 0.2716          | 0.8793 | 0.8357 | 0.8745 | 0.875     |
  | No log        | 21.0  | 441  | 0.2721          | 0.8779 | 0.8343 | 0.8733 | 0.8739    |
  | No log        | 22.0  | 462  | 0.2720          | 0.8779 | 0.8343 | 0.8733 | 0.8739    |
  | No log        | 23.0  | 483  | 0.2724          | 0.8779 | 0.8344 | 0.8734 | 0.874     |
  | 0.2699        | 24.0  | 504  | 0.2725          | 0.8783 | 0.8348 | 0.8739 | 0.8746    |
  | 0.2699        | 25.0  | 525  | 0.2721          | 0.8783 | 0.8348 | 0.8739 | 0.8746    |
  | 0.2699        | 26.0  | 546  | 0.2719          | 0.8783 | 0.8348 | 0.8739 | 0.8746    |
  | 0.2699        | 27.0  | 567  | 0.2716          | 0.8783 | 0.8348 | 0.8739 | 0.8746    |
  | 0.2699        | 28.0  | 588  | 0.2715          | 0.8783 | 0.8348 | 0.8739 | 0.8746    |
  | 0.2699        | 29.0  | 609  | 0.2716          | 0.8783 | 0.8348 | 0.8739 | 0.8746    |
  | 0.2699        | 30.0  | 630  | 0.2715          | 0.8783 | 0.8348 | 0.8739 | 0.8746    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  