readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - snli
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-contradiction
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: snli
        type: snli
        args: plain_text
      metrics:
      - name: Rouge1
        type: rouge
        value: 34.4237
  ---
  
  <!-- 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-contradiction
  
  This model is a fine-tuned version of [domenicrosati/t5-small-finetuned-contradiction](https://huggingface.co/domenicrosati/t5-small-finetuned-contradiction) on the snli dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0458
  - Rouge1: 34.4237
  - Rouge2: 14.5442
  - Rougel: 32.5483
  - Rougelsum: 32.5785
  
  ## 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: 5.6e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 1.8605        | 1.0   | 2863  | 2.0813          | 34.4597 | 14.5186 | 32.6909 | 32.7097   |
  | 1.9209        | 2.0   | 5726  | 2.0721          | 34.3859 | 14.5733 | 32.5188 | 32.5524   |
  | 1.9367        | 3.0   | 8589  | 2.0623          | 34.4192 | 14.455  | 32.581  | 32.5962   |
  | 1.9539        | 4.0   | 11452 | 2.0565          | 34.5148 | 14.6131 | 32.6786 | 32.7174   |
  | 1.9655        | 5.0   | 14315 | 2.0538          | 34.4393 | 14.6439 | 32.6344 | 32.6587   |
  | 1.9683        | 6.0   | 17178 | 2.0493          | 34.7199 | 14.7763 | 32.8625 | 32.8782   |
  | 1.9735        | 7.0   | 20041 | 2.0476          | 34.5366 | 14.6362 | 32.6939 | 32.7177   |
  | 1.98          | 8.0   | 22904 | 2.0458          | 34.5    | 14.5695 | 32.6219 | 32.6478   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  