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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- sede
model-index:
- name: t5-base-sede-txt2sql
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. -->
# t5-base-sede-txt2sql
This model is a fine-tuned version of [google/t5-v1_1-base](https://huggingface.co/google/t5-v1_1-base) on the sede dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1577
- Bleu Score: 0.5923
- Parsable Queries Accuracy: 0.0
- Partial Match F1: 0.0
- Partial Match F1 No Values: 0.0
- Partial Match Em: 0.0
- Partial Match No Values Em: 0.0
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Parsable Queries Accuracy | Partial Match F1 | Partial Match F1 No Values | Partial Match Em | Partial Match No Values Em |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:-------------------------:|:----------------:|:--------------------------:|:----------------:|:--------------------------:|
| No log | 1.0 | 95 | 13.2410 | 0.0069 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 190 | 7.6317 | 0.0134 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 285 | 6.0919 | 0.0058 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 4.0 | 380 | 5.4922 | 0.0021 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 5.0 | 475 | 4.7151 | 0.0009 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 12.0698 | 6.0 | 570 | 4.1412 | 0.0003 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 12.0698 | 7.0 | 665 | 3.6398 | 0.0003 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 12.0698 | 8.0 | 760 | 3.2643 | 0.0009 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 12.0698 | 9.0 | 855 | 3.0544 | 0.0013 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 12.0698 | 10.0 | 950 | 2.8015 | 0.0043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 4.696 | 11.0 | 1045 | 2.5552 | 0.0789 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 4.696 | 12.0 | 1140 | 2.3535 | 0.1036 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 4.696 | 13.0 | 1235 | 2.2132 | 0.0050 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 4.696 | 14.0 | 1330 | 2.1084 | 0.1333 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 4.696 | 15.0 | 1425 | 2.0117 | 0.2972 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.1348 | 16.0 | 1520 | 1.9333 | 0.2481 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.1348 | 17.0 | 1615 | 1.8395 | 0.4149 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.1348 | 18.0 | 1710 | 1.7661 | 0.5439 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.1348 | 19.0 | 1805 | 1.7101 | 0.6001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.1348 | 20.0 | 1900 | 1.6562 | 0.6219 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.1348 | 21.0 | 1995 | 1.6073 | 0.5865 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.4276 | 22.0 | 2090 | 1.5773 | 0.5683 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.4276 | 23.0 | 2185 | 1.5478 | 0.5408 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.4276 | 24.0 | 2280 | 1.5190 | 0.5749 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.4276 | 25.0 | 2375 | 1.4927 | 0.5818 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.4276 | 26.0 | 2470 | 1.4671 | 0.5673 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.076 | 27.0 | 2565 | 1.4499 | 0.5616 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.076 | 28.0 | 2660 | 1.4275 | 0.6041 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.076 | 29.0 | 2755 | 1.4096 | 0.5764 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.076 | 30.0 | 2850 | 1.3983 | 0.5862 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.076 | 31.0 | 2945 | 1.3812 | 0.5982 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.8828 | 32.0 | 3040 | 1.3679 | 0.5927 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.8828 | 33.0 | 3135 | 1.3548 | 0.5916 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.8828 | 34.0 | 3230 | 1.3461 | 0.5769 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.8828 | 35.0 | 3325 | 1.3353 | 0.5871 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.8828 | 36.0 | 3420 | 1.3293 | 0.5687 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.7602 | 37.0 | 3515 | 1.3195 | 0.5689 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.7602 | 38.0 | 3610 | 1.3109 | 0.5949 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.7602 | 39.0 | 3705 | 1.3049 | 0.5619 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.7602 | 40.0 | 3800 | 1.2953 | 0.5872 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.7602 | 41.0 | 3895 | 1.2907 | 0.6014 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.7602 | 42.0 | 3990 | 1.2831 | 0.5917 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6652 | 43.0 | 4085 | 1.2757 | 0.5718 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6652 | 44.0 | 4180 | 1.2692 | 0.5707 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6652 | 45.0 | 4275 | 1.2642 | 0.5758 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6652 | 46.0 | 4370 | 1.2619 | 0.6012 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6652 | 47.0 | 4465 | 1.2527 | 0.5749 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6009 | 48.0 | 4560 | 1.2496 | 0.5722 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6009 | 49.0 | 4655 | 1.2447 | 0.5633 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6009 | 50.0 | 4750 | 1.2411 | 0.5615 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6009 | 51.0 | 4845 | 1.2356 | 0.5691 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6009 | 52.0 | 4940 | 1.2322 | 0.5636 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5481 | 53.0 | 5035 | 1.2285 | 0.5724 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5481 | 54.0 | 5130 | 1.2255 | 0.5771 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5481 | 55.0 | 5225 | 1.2201 | 0.5827 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5481 | 56.0 | 5320 | 1.2181 | 0.5928 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5481 | 57.0 | 5415 | 1.2152 | 0.5599 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5082 | 58.0 | 5510 | 1.2123 | 0.5779 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5082 | 59.0 | 5605 | 1.2083 | 0.5609 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5082 | 60.0 | 5700 | 1.2070 | 0.5654 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5082 | 61.0 | 5795 | 1.2036 | 0.5566 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5082 | 62.0 | 5890 | 1.2011 | 0.5569 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5082 | 63.0 | 5985 | 1.1993 | 0.5567 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4799 | 64.0 | 6080 | 1.1958 | 0.5619 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4799 | 65.0 | 6175 | 1.1950 | 0.5691 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4799 | 66.0 | 6270 | 1.1914 | 0.5572 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4799 | 67.0 | 6365 | 1.1879 | 0.5635 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4799 | 68.0 | 6460 | 1.1866 | 0.5654 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4475 | 69.0 | 6555 | 1.1850 | 0.5575 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4475 | 70.0 | 6650 | 1.1833 | 0.5507 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4475 | 71.0 | 6745 | 1.1820 | 0.5493 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4475 | 72.0 | 6840 | 1.1786 | 0.5525 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4475 | 73.0 | 6935 | 1.1789 | 0.5615 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4233 | 74.0 | 7030 | 1.1770 | 0.5603 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4233 | 75.0 | 7125 | 1.1749 | 0.5699 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4233 | 76.0 | 7220 | 1.1754 | 0.5730 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4233 | 77.0 | 7315 | 1.1735 | 0.5798 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4233 | 78.0 | 7410 | 1.1716 | 0.5771 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4101 | 79.0 | 7505 | 1.1699 | 0.5800 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4101 | 80.0 | 7600 | 1.1675 | 0.5736 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4101 | 81.0 | 7695 | 1.1661 | 0.5845 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4101 | 82.0 | 7790 | 1.1659 | 0.5974 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4101 | 83.0 | 7885 | 1.1664 | 0.5825 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4101 | 84.0 | 7980 | 1.1647 | 0.5871 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3965 | 85.0 | 8075 | 1.1639 | 0.5772 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3965 | 86.0 | 8170 | 1.1628 | 0.5826 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3965 | 87.0 | 8265 | 1.1615 | 0.5960 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3965 | 88.0 | 8360 | 1.1616 | 0.5908 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3965 | 89.0 | 8455 | 1.1613 | 0.5775 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3835 | 90.0 | 8550 | 1.1604 | 0.5917 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3835 | 91.0 | 8645 | 1.1597 | 0.5732 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3835 | 92.0 | 8740 | 1.1594 | 0.5767 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3835 | 93.0 | 8835 | 1.1584 | 0.5719 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3835 | 94.0 | 8930 | 1.1581 | 0.5700 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3766 | 95.0 | 9025 | 1.1583 | 0.5845 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3766 | 96.0 | 9120 | 1.1578 | 0.5808 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3766 | 97.0 | 9215 | 1.1578 | 0.5889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3766 | 98.0 | 9310 | 1.1577 | 0.5851 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3766 | 99.0 | 9405 | 1.1578 | 0.5923 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3726 | 100.0 | 9500 | 1.1577 | 0.5923 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
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