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: 0.1245
- Rouge2 Precision: 0.8182
- Rouge2 Recall: 0.7261
- Rouge2 Fmeasure: 0.7623
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.1954 | 1.0 | 4049 | 0.1575 | 0.7935 | 0.7032 | 0.7386 |
| 0.1643 | 2.0 | 8098 | 0.1374 | 0.8084 | 0.7168 | 0.7528 |
| 0.1517 | 3.0 | 12147 | 0.1296 | 0.8136 | 0.7221 | 0.758 |
| 0.1459 | 4.0 | 16196 | 0.1256 | 0.817 | 0.7253 | 0.7613 |
| 0.1414 | 5.0 | 20245 | 0.1245 | 0.8182 | 0.7261 | 0.7623 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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