readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-pytorch-final
    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-pytorch-final
  
  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: 1.6589
  - Rouge1: 25.8199
  - Rouge2: 14.6736
  - Rougel: 22.3682
  - Rougelsum: 23.917
  - Gen Len: 19.0
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 35
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.0989        | 1.0   | 503   | 1.8152          | 24.4365 | 13.3113 | 20.9862 | 22.6351   | 19.0    |
  | 1.9704        | 2.0   | 1006  | 1.7720          | 24.8843 | 13.7084 | 21.4551 | 22.9787   | 19.0    |
  | 1.9241        | 3.0   | 1509  | 1.7468          | 25.1988 | 14.052  | 21.7041 | 23.2981   | 19.0    |
  | 1.8856        | 4.0   | 2012  | 1.7268          | 25.502  | 14.3573 | 21.9449 | 23.5741   | 19.0    |
  | 1.8653        | 5.0   | 2515  | 1.7156          | 25.6461 | 14.3872 | 22.0824 | 23.6502   | 19.0    |
  | 1.8367        | 6.0   | 3018  | 1.7057          | 25.6513 | 14.4842 | 22.2314 | 23.7009   | 19.0    |
  | 1.8183        | 7.0   | 3521  | 1.6993          | 25.6377 | 14.481  | 22.185  | 23.6855   | 19.0    |
  | 1.8068        | 8.0   | 4024  | 1.6945          | 25.5275 | 14.3184 | 22.03   | 23.5524   | 19.0    |
  | 1.7959        | 9.0   | 4527  | 1.6885          | 25.4232 | 14.2443 | 21.9691 | 23.4711   | 19.0    |
  | 1.7741        | 10.0  | 5030  | 1.6840          | 25.5169 | 14.2654 | 22.0518 | 23.5864   | 19.0    |
  | 1.7665        | 11.0  | 5533  | 1.6817          | 25.5237 | 14.3758 | 22.094  | 23.5891   | 19.0    |
  | 1.7541        | 12.0  | 6036  | 1.6779          | 25.2572 | 14.1939 | 21.816  | 23.3577   | 19.0    |
  | 1.7479        | 13.0  | 6539  | 1.6761          | 25.3922 | 14.4173 | 22.0299 | 23.5163   | 19.0    |
  | 1.7308        | 14.0  | 7042  | 1.6742          | 25.3631 | 14.2906 | 22.0221 | 23.5128   | 19.0    |
  | 1.7261        | 15.0  | 7545  | 1.6717          | 25.4318 | 14.3493 | 22.0454 | 23.5278   | 19.0    |
  | 1.7181        | 16.0  | 8048  | 1.6691          | 25.4043 | 14.325  | 22.0252 | 23.5423   | 19.0    |
  | 1.7048        | 17.0  | 8551  | 1.6691          | 25.6406 | 14.5424 | 22.2377 | 23.7325   | 19.0    |
  | 1.7064        | 18.0  | 9054  | 1.6671          | 25.4986 | 14.3177 | 22.0629 | 23.5943   | 19.0    |
  | 1.7003        | 19.0  | 9557  | 1.6687          | 25.6196 | 14.4546 | 22.2079 | 23.7184   | 19.0    |
  | 1.6858        | 20.0  | 10060 | 1.6660          | 25.6864 | 14.5874 | 22.3071 | 23.8151   | 19.0    |
  | 1.6861        | 21.0  | 10563 | 1.6648          | 25.6698 | 14.5281 | 22.2717 | 23.797    | 19.0    |
  | 1.684         | 22.0  | 11066 | 1.6635          | 25.7104 | 14.5393 | 22.2573 | 23.829    | 19.0    |
  | 1.6751        | 23.0  | 11569 | 1.6615          | 25.7254 | 14.5923 | 22.2509 | 23.8439   | 19.0    |
  | 1.6741        | 24.0  | 12072 | 1.6624          | 25.7821 | 14.663  | 22.3164 | 23.8809   | 19.0    |
  | 1.6765        | 25.0  | 12575 | 1.6621          | 25.7689 | 14.5796 | 22.2779 | 23.8765   | 19.0    |
  | 1.6562        | 26.0  | 13078 | 1.6616          | 25.7856 | 14.6224 | 22.3298 | 23.9215   | 19.0    |
  | 1.6636        | 27.0  | 13581 | 1.6610          | 25.83   | 14.6569 | 22.4229 | 23.9404   | 19.0    |
  | 1.671         | 28.0  | 14084 | 1.6599          | 25.6857 | 14.5126 | 22.2093 | 23.788    | 19.0    |
  | 1.6467        | 29.0  | 14587 | 1.6602          | 25.8111 | 14.6784 | 22.3599 | 23.9132   | 19.0    |
  | 1.6556        | 30.0  | 15090 | 1.6594          | 25.8887 | 14.7244 | 22.3998 | 23.9739   | 19.0    |
  | 1.6463        | 31.0  | 15593 | 1.6594          | 25.8534 | 14.6966 | 22.3867 | 23.9439   | 19.0    |
  | 1.6548        | 32.0  | 16096 | 1.6600          | 25.839  | 14.674  | 22.3763 | 23.9438   | 19.0    |
  | 1.6458        | 33.0  | 16599 | 1.6590          | 25.8364 | 14.6589 | 22.3512 | 23.9243   | 19.0    |
  | 1.6431        | 34.0  | 17102 | 1.6590          | 25.8314 | 14.6733 | 22.3526 | 23.9288   | 19.0    |
  | 1.6637        | 35.0  | 17605 | 1.6589          | 25.8199 | 14.6736 | 22.3682 | 23.917    | 19.0    |
  