readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - scitldr
  metrics:
  - rouge
  model-index:
  - name: paper-summary
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: scitldr
        type: scitldr
        config: Abstract
        split: train
        args: Abstract
      metrics:
      - name: Rouge1
        type: rouge
        value: 0.3484
  ---
  
  <!-- 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. -->
  
  # paper-summary
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the scitldr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8631
  - Rouge1: 0.3484
  - Rouge2: 0.1596
  - Rougel: 0.2971
  - Rougelsum: 0.3047
  
  ## 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: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 3.0545        | 1.0   | 63   | 2.9939          | 0.3387 | 0.1538 | 0.2887 | 0.2957    |
  | 2.7871        | 2.0   | 126  | 2.9360          | 0.3448 | 0.1577 | 0.2947 | 0.3019    |
  | 2.7188        | 3.0   | 189  | 2.8977          | 0.3477 | 0.1585 | 0.2967 | 0.3035    |
  | 2.6493        | 4.0   | 252  | 2.8837          | 0.3488 | 0.1597 | 0.2973 | 0.3046    |
  | 2.6207        | 5.0   | 315  | 2.8690          | 0.3472 | 0.1566 | 0.2958 | 0.3033    |
  | 2.5893        | 6.0   | 378  | 2.8668          | 0.3493 | 0.1592 | 0.2972 | 0.305     |
  | 2.5494        | 7.0   | 441  | 2.8657          | 0.3486 | 0.1595 | 0.2976 | 0.3053    |
  | 2.5554        | 8.0   | 504  | 2.8631          | 0.3484 | 0.1596 | 0.2971 | 0.3047    |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  