readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-pubmed
    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-pubmed
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on a truncated [PubMed Summarization](https://huggingface.co/datasets/ccdv/pubmed-summarization) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.7252
  - Rouge1: 19.4457
  - Rouge2: 3.125
  - Rougel: 18.3168
  - Rougelsum: 18.5625
  
  ## 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: 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: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 3.2735        | 1.0   | 13   | 2.9820          | 18.745  | 3.7918 | 15.7876 | 15.8512   |
  | 3.0428        | 2.0   | 26   | 2.8828          | 17.953  | 2.5    | 15.49   | 15.468    |
  | 2.6259        | 3.0   | 39   | 2.8283          | 21.5532 | 5.9278 | 19.7523 | 19.9232   |
  | 3.0795        | 4.0   | 52   | 2.7910          | 20.9244 | 5.9278 | 19.8685 | 20.0181   |
  | 2.8276        | 5.0   | 65   | 2.7613          | 20.6403 | 3.125  | 18.0574 | 18.2227   |
  | 2.64          | 6.0   | 78   | 2.7404          | 19.4457 | 3.125  | 18.3168 | 18.5625   |
  | 2.5525        | 7.0   | 91   | 2.7286          | 19.4457 | 3.125  | 18.3168 | 18.5625   |
  | 2.4951        | 8.0   | 104  | 2.7252          | 19.4457 | 3.125  | 18.3168 | 18.5625   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  