readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - amazon_reviews_multi
  model-index:
  - name: jjung
    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. -->
  
  # jjung
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the amazon_reviews_multi dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.7957
  - Rouge1 Fmeasure: 0.1754
  - Rouge1 Precision: 0.1858
  - Rouge1 Recall: 0.2063
  - Rouge2 Fmeasure: 0.0746
  - Rouge2 Precision: 0.0760
  - Rouge2 Recall: 0.0857
  - Rougel Fmeasure: 0.1722
  - Rougel Precision: 0.1810
  - Rougel Recall: 0.2028
  - Rougelsum Fmeasure: 0.1722
  - Rougelsum Precision: 0.1810
  - Rougelsum Recall: 0.2028
  
  ## 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 Fmeasure | Rouge1 Precision | Rouge1 Recall | Rouge2 Fmeasure | Rouge2 Precision | Rouge2 Recall | Rougel Fmeasure | Rougel Precision | Rougel Recall | Rougelsum Fmeasure | Rougelsum Precision | Rougelsum Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:------------------:|:-------------------:|:----------------:|
  | 2.8948        | 1.0   | 1314  | 2.7371          | 0.1548          | 0.1748           | 0.1855        | 0.0654          | 0.0666           | 0.0769        | 0.1522          | 0.1704           | 0.1827        | 0.1522             | 0.1704              | 0.1827           |
  | 2.5527        | 2.0   | 2628  | 2.6921          | 0.1653          | 0.1826           | 0.1858        | 0.0625          | 0.0642           | 0.0732        | 0.1623          | 0.1783           | 0.1830        | 0.1623             | 0.1783              | 0.1830           |
  | 2.3646        | 3.0   | 3942  | 2.6950          | 0.1767          | 0.1893           | 0.2063        | 0.0739          | 0.0735           | 0.0913        | 0.1737          | 0.1847           | 0.2030        | 0.1737             | 0.1847              | 0.2030           |
  | 2.2218        | 4.0   | 5256  | 2.7185          | 0.1870          | 0.1954           | 0.2180        | 0.0816          | 0.0840           | 0.0937        | 0.1844          | 0.1925           | 0.2150        | 0.1844             | 0.1925              | 0.2150           |
  | 2.11          | 5.0   | 6570  | 2.7495          | 0.1669          | 0.1771           | 0.2022        | 0.0687          | 0.0666           | 0.0864        | 0.1624          | 0.1712           | 0.1975        | 0.1624             | 0.1712              | 0.1975           |
  | 2.027         | 6.0   | 7884  | 2.7691          | 0.1752          | 0.1859           | 0.2064        | 0.0726          | 0.0725           | 0.0839        | 0.1712          | 0.1803           | 0.2023        | 0.1712             | 0.1803              | 0.2023           |
  | 1.9679        | 7.0   | 9198  | 2.7844          | 0.1634          | 0.1731           | 0.1926        | 0.0646          | 0.0635           | 0.0778        | 0.1601          | 0.1684           | 0.1890        | 0.1601             | 0.1684              | 0.1890           |
  | 1.9181        | 8.0   | 10512 | 2.7957          | 0.1754          | 0.1858           | 0.2063        | 0.0746          | 0.0760           | 0.0857        | 0.1722          | 0.1810           | 0.2028        | 0.1722             | 0.1810              | 0.2028           |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.12.1
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  