T5Training
This model is a fine-tuned version of t5-base on the wikisql dataset. It achieves the following results on the evaluation set:
- Loss: 0.0341
- Rouge2 Precision: 0.9368
- Rouge2 Recall: 0.8687
- Rouge2 Fmeasure: 0.896
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 |
|---|---|---|---|---|---|---|
| 0.0225 | 1.0 | 4049 | 0.0355 | 0.9325 | 0.8665 | 0.8929 |
| 0.0182 | 2.0 | 8098 | 0.0359 | 0.9364 | 0.8682 | 0.8956 |
| 0.016 | 3.0 | 12147 | 0.0354 | 0.9353 | 0.868 | 0.895 |
| 0.0156 | 4.0 | 16196 | 0.0351 | 0.9366 | 0.8684 | 0.8958 |
| 0.0177 | 5.0 | 20245 | 0.0341 | 0.9368 | 0.8687 | 0.896 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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