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t5-small-finetuned-wikisql
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1165
- Rouge2 Precision: 0.8267
- Rouge2 Recall: 0.7345
- Rouge2 Fmeasure: 0.7706
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: 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 |
|---|---|---|---|---|---|---|
| 0.2196 | 1.0 | 3569 | 0.1709 | 0.7843 | 0.6963 | 0.7307 |
| 0.1767 | 2.0 | 7138 | 0.1480 | 0.8031 | 0.7118 | 0.7477 |
| 0.1614 | 3.0 | 10707 | 0.1353 | 0.8115 | 0.72 | 0.7559 |
| 0.148 | 4.0 | 14276 | 0.1287 | 0.8165 | 0.7244 | 0.7604 |
| 0.1406 | 5.0 | 17845 | 0.1242 | 0.8207 | 0.7283 | 0.7646 |
| 0.1337 | 6.0 | 21414 | 0.1209 | 0.8238 | 0.7313 | 0.7676 |
| 0.1296 | 7.0 | 24983 | 0.1193 | 0.8252 | 0.7329 | 0.7691 |
| 0.1271 | 8.0 | 28552 | 0.1177 | 0.825 | 0.7329 | 0.7691 |
| 0.1222 | 9.0 | 32121 | 0.1167 | 0.8262 | 0.7341 | 0.7702 |
| 0.1229 | 10.0 | 35690 | 0.1165 | 0.8267 | 0.7345 | 0.7706 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
