readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wikisql
  model-index:
  - name: t5-small-finetuned-wikisql
    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-wikisql
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikisql dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1242
  - Rouge2 Precision: 0.8193
  - Rouge2 Recall: 0.7267
  - Rouge2 Fmeasure: 0.7631
  
  ## 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: 5e-05
  - 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.2718        | 1.0   | 2025  | 0.2103          | 0.7551           | 0.6695        | 0.7026          |
  | 0.2172        | 2.0   | 4050  | 0.1762          | 0.7779           | 0.6893        | 0.7237          |
  | 0.1982        | 3.0   | 6075  | 0.1608          | 0.7918           | 0.7014        | 0.7369          |
  | 0.183         | 4.0   | 8100  | 0.1504          | 0.8006           | 0.71          | 0.7456          |
  | 0.1702        | 5.0   | 10125 | 0.1433          | 0.8052           | 0.7137        | 0.7497          |
  | 0.1631        | 6.0   | 12150 | 0.1378          | 0.8086           | 0.7166        | 0.7529          |
  | 0.1575        | 7.0   | 14175 | 0.1336          | 0.8123           | 0.7203        | 0.7566          |
  | 0.152         | 8.0   | 16200 | 0.1300          | 0.8154           | 0.7234        | 0.7597          |
  | 0.1458        | 9.0   | 18225 | 0.1266          | 0.8171           | 0.7251        | 0.7613          |
  | 0.1422        | 10.0  | 20250 | 0.1242          | 0.8193           | 0.7267        | 0.7631          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  