readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - pub_med_summarization_dataset
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-pubmed
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: pub_med_summarization_dataset
        type: pub_med_summarization_dataset
        args: document
      metrics:
      - name: Rouge1
        type: rouge
        value: 8.8295
  ---
  
  <!-- 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-pubmed
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the pub_med_summarization_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.2635
  - Rouge1: 8.8295
  - Rouge2: 3.2594
  - Rougel: 7.9975
  - Rougelsum: 8.4483
  - 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: 2
  - eval_batch_size: 2
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:|
  | 2.5892        | 1.0   | 4000  | 2.3616          | 10.1169 | 3.9666 | 8.8854 | 9.5836    | 19.0    |
  | 2.559         | 2.0   | 8000  | 2.3045          | 9.4321  | 3.5398 | 8.424  | 8.984     | 19.0    |
  | 2.5029        | 3.0   | 12000 | 2.2820          | 9.1658  | 3.3686 | 8.2222 | 8.7311    | 19.0    |
  | 2.4673        | 4.0   | 16000 | 2.2692          | 8.8973  | 3.2617 | 8.0395 | 8.5046    | 19.0    |
  | 2.4331        | 5.0   | 20000 | 2.2635          | 8.8295  | 3.2594 | 7.9975 | 8.4483    | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  