readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  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-base](https://huggingface.co/t5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2640
  - Rouge2 Precision: 0.8471
  - Rouge2 Recall: 0.3841
  - Rouge2 Fmeasure: 0.5064
  
  ## 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: 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | No log        | 1.0   | 11   | 2.7587          | 0.098            | 0.0305        | 0.045           |
  | No log        | 2.0   | 22   | 2.0056          | 0.0969           | 0.0284        | 0.0422          |
  | No log        | 3.0   | 33   | 1.4456          | 0.1046           | 0.0349        | 0.0503          |
  | No log        | 4.0   | 44   | 1.0317          | 0.1054           | 0.0337        | 0.0482          |
  | No log        | 5.0   | 55   | 0.7603          | 0.2749           | 0.1299        | 0.1724          |
  | No log        | 6.0   | 66   | 0.5722          | 0.7115           | 0.352         | 0.4552          |
  | No log        | 7.0   | 77   | 0.4751          | 0.6872           | 0.337         | 0.436           |
  | No log        | 8.0   | 88   | 0.4253          | 0.7256           | 0.3439        | 0.4462          |
  | No log        | 9.0   | 99   | 0.3805          | 0.7335           | 0.3204        | 0.4308          |
  | No log        | 10.0  | 110  | 0.3562          | 0.7342           | 0.3239        | 0.433           |
  | No log        | 11.0  | 121  | 0.3275          | 0.7906           | 0.355         | 0.471           |
  | No log        | 12.0  | 132  | 0.3133          | 0.8382           | 0.3838        | 0.5061          |
  | No log        | 13.0  | 143  | 0.2996          | 0.8409           | 0.3841        | 0.5062          |
  | No log        | 14.0  | 154  | 0.2903          | 0.8304           | 0.3763        | 0.4978          |
  | No log        | 15.0  | 165  | 0.2867          | 0.8409           | 0.3841        | 0.5062          |
  | No log        | 16.0  | 176  | 0.2786          | 0.8409           | 0.3841        | 0.5062          |
  | No log        | 17.0  | 187  | 0.2711          | 0.8409           | 0.3841        | 0.5062          |
  | No log        | 18.0  | 198  | 0.2673          | 0.8409           | 0.3841        | 0.5062          |
  | No log        | 19.0  | 209  | 0.2643          | 0.8471           | 0.3841        | 0.5064          |
  | No log        | 20.0  | 220  | 0.2640          | 0.8471           | 0.3841        | 0.5064          |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  