EN_t5-base_5_wikiSQL_sch
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0120
- Rouge2 Precision: 0.9364
- Rouge2 Recall: 0.8382
- Rouge2 Fmeasure: 0.8771
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 |
|---|---|---|---|---|---|---|
| 0.0199 | 1.0 | 4049 | 0.0150 | 0.9263 | 0.8311 | 0.8685 |
| 0.015 | 2.0 | 8098 | 0.0131 | 0.9338 | 0.8353 | 0.8743 |
| 0.0128 | 3.0 | 12147 | 0.0123 | 0.9353 | 0.8366 | 0.8758 |
| 0.011 | 4.0 | 16196 | 0.0121 | 0.9358 | 0.8381 | 0.8768 |
| 0.0098 | 5.0 | 20245 | 0.0120 | 0.9364 | 0.8382 | 0.8771 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1