readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-xlsum-with-multi-news-10-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-10-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: 2.2332
  - Rouge1: 31.4802
  - Rouge2: 9.9475
  - Rougel: 24.6687
  - Rougelsum: 24.7013
  - Gen Len: 18.8025
  
  ## 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.7314        | 1.0   | 20543  | 2.3867          | 29.3997 | 8.2875 | 22.8406 | 22.8871   | 18.8204 |
  | 2.6652        | 2.0   | 41086  | 2.3323          | 30.3992 | 8.9058 | 23.6168 | 23.6626   | 18.8447 |
  | 2.632         | 3.0   | 61629  | 2.3002          | 30.8662 | 9.2869 | 24.0683 | 24.11     | 18.8122 |
  | 2.6221        | 4.0   | 82172  | 2.2785          | 31.143  | 9.5737 | 24.3473 | 24.381    | 18.7911 |
  | 2.5925        | 5.0   | 102715 | 2.2631          | 31.2144 | 9.6904 | 24.4419 | 24.4796   | 18.8133 |
  | 2.5812        | 6.0   | 123258 | 2.2507          | 31.3371 | 9.7959 | 24.5801 | 24.6166   | 18.7836 |
  | 2.5853        | 7.0   | 143801 | 2.2437          | 31.3593 | 9.8156 | 24.5533 | 24.5852   | 18.8103 |
  | 2.5467        | 8.0   | 164344 | 2.2377          | 31.368  | 9.8807 | 24.6226 | 24.6518   | 18.799  |
  | 2.5571        | 9.0   | 184887 | 2.2337          | 31.4356 | 9.9092 | 24.6543 | 24.6891   | 18.8075 |
  | 2.5563        | 10.0  | 205430 | 2.2332          | 31.4802 | 9.9475 | 24.6687 | 24.7013   | 18.8025 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.13.1+cpu
  - Datasets 2.8.0
  - Tokenizers 0.10.3
  