readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - scientific_papers
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-xsum-xlsum
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: scientific_papers
        type: scientific_papers
        config: pubmed
        split: train
        args: pubmed
      metrics:
      - name: Rouge1
        type: rouge
        value: 14.3541
  ---
  
  <!-- 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-xsum-xlsum
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the scientific_papers dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9963
  - Rouge1: 14.3541
  - Rouge2: 6.1674
  - Rougel: 12.2975
  - Rougelsum: 13.2515
  - 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: 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.3055        | 1.0   | 7496  | 2.0773          | 14.3312 | 6.153  | 12.2551 | 13.2033   | 19.0    |
  | 2.2512        | 2.0   | 14992 | 2.0330          | 14.3048 | 6.1346 | 12.2343 | 13.1992   | 19.0    |
  | 2.2034        | 3.0   | 22488 | 2.0106          | 14.3866 | 6.1752 | 12.3205 | 13.2743   | 19.0    |
  | 2.2054        | 4.0   | 29984 | 2.0004          | 14.3629 | 6.167  | 12.2928 | 13.2506   | 19.0    |
  | 2.1944        | 5.0   | 37480 | 1.9963          | 14.3541 | 6.1674 | 12.2975 | 13.2515   | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  