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: 0.1271
- Rouge2 Precision: 0.8165
- Rouge2 Recall: 0.7252
- Rouge2 Fmeasure: 0.761
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 |
---|---|---|---|---|---|---|
0.2002 | 1.0 | 4049 | 0.1609 | 0.7909 | 0.7013 | 0.7363 |
0.1681 | 2.0 | 8098 | 0.1407 | 0.8055 | 0.7143 | 0.7501 |
0.155 | 3.0 | 12147 | 0.1325 | 0.8119 | 0.7209 | 0.7566 |
0.1498 | 4.0 | 16196 | 0.1285 | 0.8156 | 0.7246 | 0.7604 |
0.145 | 5.0 | 20245 | 0.1271 | 0.8165 | 0.7252 | 0.761 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
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