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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: 1.7557
- Rouge2 Precision: 0.0052
- Rouge2 Recall: 0.0036
- Rouge2 Fmeasure: 0.0041
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 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 2.7037 | 0.0087 | 0.009 | 0.0086 |
| No log | 2.0 | 14 | 1.9702 | 0.0037 | 0.0032 | 0.0031 |
| No log | 3.0 | 21 | 1.8608 | 0.004 | 0.0032 | 0.0033 |
| No log | 4.0 | 28 | 1.7833 | 0.0042 | 0.0032 | 0.0035 |
| No log | 5.0 | 35 | 1.7557 | 0.0052 | 0.0036 | 0.0041 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Tokenizers 0.13.2
