t5-small-finetuned-wikisql
This model is a fine-tuned version of t5-small on the wikisql dataset. It achieves the following results on the evaluation set:
- Loss: 0.1237
- Rouge2 Precision: 0.8197
- Rouge2 Recall: 0.7427
- Rouge2 Fmeasure: 0.773
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.1885 | 1.0 | 4049 | 0.1513 | 0.7962 | 0.721 | 0.7504 |
| 0.1623 | 2.0 | 8098 | 0.1362 | 0.8107 | 0.7331 | 0.7637 |
| 0.1453 | 3.0 | 12147 | 0.1284 | 0.8168 | 0.7388 | 0.7697 |
| 0.1401 | 4.0 | 16196 | 0.1247 | 0.8179 | 0.7409 | 0.7712 |
| 0.1391 | 5.0 | 20245 | 0.1237 | 0.8197 | 0.7427 | 0.773 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.0