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---
base_model: TeeA/T5-Text2SQL-Bilingual
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Text2SQL-Bilingual
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Text2SQL-Bilingual
This model is a fine-tuned version of [TeeA/T5-Text2SQL-Bilingual](https://huggingface.co/TeeA/T5-Text2SQL-Bilingual) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0018
- Rouge1: 0.8820
- Rouge2: 0.8188
- Rougel: 0.8750
- Rougelsum: 0.8750
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.3182 | 1.0 | 4389 | 1.2317 | 0.8648 | 0.7817 | 0.8552 | 0.8551 |
| 1.2945 | 2.0 | 8778 | 1.2231 | 0.8647 | 0.7827 | 0.8562 | 0.8566 |
| 1.2952 | 3.0 | 13167 | 1.2126 | 0.8680 | 0.7884 | 0.8590 | 0.8589 |
| 1.2712 | 4.0 | 17556 | 1.1972 | 0.8651 | 0.7855 | 0.8566 | 0.8566 |
| 1.2547 | 5.0 | 21945 | 1.1891 | 0.8703 | 0.7916 | 0.8608 | 0.8611 |
| 1.2414 | 6.0 | 26334 | 1.1771 | 0.8709 | 0.7942 | 0.8621 | 0.8618 |
| 1.2111 | 7.0 | 30723 | 1.1675 | 0.8719 | 0.7964 | 0.8640 | 0.8641 |
| 1.2218 | 8.0 | 35112 | 1.1567 | 0.8699 | 0.7932 | 0.8620 | 0.8619 |
| 1.2086 | 9.0 | 39501 | 1.1489 | 0.8739 | 0.7999 | 0.8655 | 0.8654 |
| 1.1895 | 10.0 | 43890 | 1.1390 | 0.8724 | 0.7992 | 0.8657 | 0.8655 |
| 1.1916 | 11.0 | 48279 | 1.1305 | 0.8757 | 0.8012 | 0.8679 | 0.8678 |
| 1.1837 | 12.0 | 52668 | 1.1208 | 0.8750 | 0.8025 | 0.8677 | 0.8673 |
| 1.169 | 13.0 | 57057 | 1.1146 | 0.8774 | 0.8069 | 0.8705 | 0.8702 |
| 1.1581 | 14.0 | 61446 | 1.1097 | 0.8772 | 0.8075 | 0.8705 | 0.8702 |
| 1.1552 | 15.0 | 65835 | 1.1028 | 0.8769 | 0.8062 | 0.8698 | 0.8697 |
| 1.1628 | 16.0 | 70224 | 1.0941 | 0.8765 | 0.8051 | 0.8692 | 0.8695 |
| 1.1429 | 17.0 | 74613 | 1.0869 | 0.8780 | 0.8077 | 0.8705 | 0.8707 |
| 1.1403 | 18.0 | 79002 | 1.0827 | 0.8786 | 0.8107 | 0.8715 | 0.8715 |
| 1.114 | 19.0 | 83391 | 1.0781 | 0.8796 | 0.8101 | 0.8714 | 0.8716 |
| 1.1131 | 20.0 | 87780 | 1.0738 | 0.8797 | 0.8116 | 0.8720 | 0.8723 |
| 1.1205 | 21.0 | 92169 | 1.0679 | 0.8791 | 0.8110 | 0.8718 | 0.8719 |
| 1.1089 | 22.0 | 96558 | 1.0647 | 0.8781 | 0.8105 | 0.8702 | 0.8706 |
| 1.0958 | 23.0 | 100947 | 1.0583 | 0.8776 | 0.8095 | 0.8706 | 0.8707 |
| 1.0923 | 24.0 | 105336 | 1.0546 | 0.8803 | 0.8130 | 0.8729 | 0.8730 |
| 1.0974 | 25.0 | 109725 | 1.0491 | 0.8786 | 0.8104 | 0.8718 | 0.8719 |
| 1.0942 | 26.0 | 114114 | 1.0465 | 0.8819 | 0.8168 | 0.8755 | 0.8753 |
| 1.0719 | 27.0 | 118503 | 1.0434 | 0.8789 | 0.8122 | 0.8715 | 0.8714 |
| 1.0786 | 28.0 | 122892 | 1.0397 | 0.8795 | 0.8134 | 0.8721 | 0.8723 |
| 1.0789 | 29.0 | 127281 | 1.0368 | 0.8791 | 0.8124 | 0.8717 | 0.8718 |
| 1.0567 | 30.0 | 131670 | 1.0331 | 0.8815 | 0.8165 | 0.8752 | 0.8753 |
| 1.0708 | 31.0 | 136059 | 1.0298 | 0.8793 | 0.8143 | 0.8728 | 0.8727 |
| 1.0601 | 32.0 | 140448 | 1.0249 | 0.8794 | 0.8148 | 0.8731 | 0.8731 |
| 1.0573 | 33.0 | 144837 | 1.0247 | 0.8790 | 0.8159 | 0.8729 | 0.8729 |
| 1.0586 | 34.0 | 149226 | 1.0202 | 0.8783 | 0.8143 | 0.8720 | 0.8719 |
| 1.0569 | 35.0 | 153615 | 1.0179 | 0.8807 | 0.8172 | 0.8738 | 0.8737 |
| 1.0591 | 36.0 | 158004 | 1.0168 | 0.8803 | 0.8156 | 0.8733 | 0.8734 |
| 1.0579 | 37.0 | 162393 | 1.0153 | 0.8808 | 0.8170 | 0.8741 | 0.8738 |
| 1.0401 | 38.0 | 166782 | 1.0129 | 0.8801 | 0.8170 | 0.8736 | 0.8736 |
| 1.0316 | 39.0 | 171171 | 1.0110 | 0.8802 | 0.8166 | 0.8733 | 0.8733 |
| 1.0264 | 40.0 | 175560 | 1.0091 | 0.8814 | 0.8181 | 0.8744 | 0.8744 |
| 1.051 | 41.0 | 179949 | 1.0066 | 0.8801 | 0.8174 | 0.8733 | 0.8731 |
| 1.0365 | 42.0 | 184338 | 1.0059 | 0.8823 | 0.8196 | 0.8754 | 0.8753 |
| 1.054 | 43.0 | 188727 | 1.0049 | 0.8805 | 0.8169 | 0.8734 | 0.8735 |
| 1.0287 | 44.0 | 193116 | 1.0051 | 0.8839 | 0.8216 | 0.8769 | 0.8769 |
| 1.0293 | 45.0 | 197505 | 1.0040 | 0.8837 | 0.8209 | 0.8769 | 0.8770 |
| 1.0315 | 46.0 | 201894 | 1.0025 | 0.8820 | 0.8184 | 0.8751 | 0.8751 |
| 1.0362 | 47.0 | 206283 | 1.0022 | 0.8820 | 0.8191 | 0.8754 | 0.8754 |
| 1.0291 | 48.0 | 210672 | 1.0015 | 0.8824 | 0.8192 | 0.8751 | 0.8752 |
| 1.0246 | 49.0 | 215061 | 1.0019 | 0.8821 | 0.8192 | 0.8752 | 0.8753 |
| 1.0355 | 50.0 | 219450 | 1.0018 | 0.8820 | 0.8188 | 0.8750 | 0.8750 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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