readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-xlsum-with-multi-news-test-5-epoch
    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-xlsum-with-multi-news-test-5-epoch
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.2989
  - Rouge1: 30.8254
  - Rouge2: 9.2466
  - Rougel: 24.0068
  - Rougelsum: 24.0535
  - Gen Len: 18.8143
  
  ## 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: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.7346        | 1.0   | 20543  | 2.3901          | 29.3586 | 8.2361 | 22.7798 | 22.8273   | 18.8201 |
  | 2.6739        | 2.0   | 41086  | 2.3414          | 30.2258 | 8.77   | 23.496  | 23.5405   | 18.8384 |
  | 2.6486        | 3.0   | 61629  | 2.3160          | 30.6221 | 9.1072 | 23.8114 | 23.8584   | 18.8194 |
  | 2.648         | 4.0   | 82172  | 2.3033          | 30.8171 | 9.2146 | 23.9993 | 24.0424   | 18.8016 |
  | 2.63          | 5.0   | 102715 | 2.2989          | 30.8254 | 9.2466 | 24.0068 | 24.0535   | 18.8143 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.13.1+cpu
  - Datasets 2.8.0
  - Tokenizers 0.10.3
  