EN_t5-small_10_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: 0.1096
- Rouge2 Precision: 0.8329
- Rouge2 Recall: 0.741
- Rouge2 Fmeasure: 0.7772
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 |
|---|---|---|---|---|---|---|
| 0.1933 | 1.0 | 4049 | 0.1549 | 0.7965 | 0.7075 | 0.7423 |
| 0.161 | 2.0 | 8098 | 0.1345 | 0.8123 | 0.7211 | 0.7569 |
| 0.1459 | 3.0 | 12147 | 0.1256 | 0.8165 | 0.7253 | 0.7611 |
| 0.1371 | 4.0 | 16196 | 0.1194 | 0.8236 | 0.7321 | 0.7681 |
| 0.1293 | 5.0 | 20245 | 0.1159 | 0.8275 | 0.7355 | 0.7718 |
| 0.1243 | 6.0 | 24294 | 0.1135 | 0.8283 | 0.7356 | 0.7722 |
| 0.1245 | 7.0 | 28343 | 0.1116 | 0.831 | 0.7383 | 0.7748 |
| 0.1167 | 8.0 | 32392 | 0.1104 | 0.8325 | 0.7401 | 0.7765 |
| 0.1134 | 9.0 | 36441 | 0.1097 | 0.8325 | 0.7408 | 0.7769 |
| 0.1131 | 10.0 | 40490 | 0.1096 | 0.8329 | 0.741 | 0.7772 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3