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t5-text2sql_v1

Text2Text Generation
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PyTorch
TensorBoard
t5
Generated from Trainer
text-generation-inference
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update model card README.md

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  ---
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- license: apache-2.0
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -12,12 +11,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # t5-text2sql_v1
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- This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0747
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- - Rouge2 Precision: 0.9499
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- - Rouge2 Recall: 0.3287
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- - Rouge2 Fmeasure: 0.4614
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  ## Model description
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@@ -48,36 +47,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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- | No log | 1.0 | 11 | 2.1363 | 0.0465 | 0.0105 | 0.017 |
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- | No log | 2.0 | 22 | 1.3415 | 0.0475 | 0.0105 | 0.017 |
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- | No log | 3.0 | 33 | 0.8590 | 0.0445 | 0.0119 | 0.0181 |
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- | No log | 4.0 | 44 | 0.5496 | 0.2211 | 0.0848 | 0.1182 |
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- | No log | 5.0 | 55 | 0.3879 | 0.4371 | 0.1923 | 0.2529 |
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- | No log | 6.0 | 66 | 0.2915 | 0.7201 | 0.259 | 0.3604 |
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- | No log | 7.0 | 77 | 0.2325 | 0.7942 | 0.2704 | 0.3838 |
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- | No log | 8.0 | 88 | 0.1910 | 0.8412 | 0.288 | 0.4067 |
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- | No log | 9.0 | 99 | 0.1734 | 0.8399 | 0.2964 | 0.4132 |
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- | No log | 10.0 | 110 | 0.1453 | 0.8902 | 0.3211 | 0.4448 |
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- | No log | 11.0 | 121 | 0.1276 | 0.8749 | 0.3121 | 0.434 |
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- | No log | 12.0 | 132 | 0.1236 | 0.8486 | 0.304 | 0.423 |
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- | No log | 13.0 | 143 | 0.1173 | 0.8369 | 0.301 | 0.4178 |
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- | No log | 14.0 | 154 | 0.1085 | 0.8935 | 0.3147 | 0.4411 |
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- | No log | 15.0 | 165 | 0.1001 | 0.9154 | 0.3216 | 0.452 |
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- | No log | 16.0 | 176 | 0.0971 | 0.8822 | 0.3155 | 0.4402 |
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- | No log | 17.0 | 187 | 0.0931 | 0.9071 | 0.3247 | 0.4525 |
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- | No log | 18.0 | 198 | 0.0870 | 0.9029 | 0.3174 | 0.4453 |
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- | No log | 19.0 | 209 | 0.0838 | 0.9286 | 0.323 | 0.4545 |
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- | No log | 20.0 | 220 | 0.0842 | 0.9539 | 0.3328 | 0.4667 |
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- | No log | 21.0 | 231 | 0.0824 | 0.9539 | 0.3328 | 0.4667 |
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- | No log | 22.0 | 242 | 0.0801 | 0.9539 | 0.3311 | 0.465 |
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- | No log | 23.0 | 253 | 0.0789 | 0.9316 | 0.321 | 0.4507 |
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- | No log | 24.0 | 264 | 0.0778 | 0.9316 | 0.321 | 0.4507 |
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- | No log | 25.0 | 275 | 0.0768 | 0.9316 | 0.3194 | 0.449 |
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- | No log | 26.0 | 286 | 0.0762 | 0.9338 | 0.3222 | 0.4523 |
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- | No log | 27.0 | 297 | 0.0755 | 0.9499 | 0.3287 | 0.4614 |
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- | No log | 28.0 | 308 | 0.0752 | 0.9499 | 0.3287 | 0.4614 |
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- | No log | 29.0 | 319 | 0.0749 | 0.9499 | 0.3287 | 0.4614 |
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- | No log | 30.0 | 330 | 0.0747 | 0.9499 | 0.3287 | 0.4614 |
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  ### Framework versions
 
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  ---
 
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # t5-text2sql_v1
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+ This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1192
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+ - Rouge2 Precision: 0.7957
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+ - Rouge2 Recall: 0.1732
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+ - Rouge2 Fmeasure: 0.2797
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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+ | No log | 1.0 | 68 | 0.4893 | 0.5045 | 0.1277 | 0.2011 |
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+ | No log | 2.0 | 136 | 0.3149 | 0.6629 | 0.1483 | 0.2391 |
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+ | No log | 3.0 | 204 | 0.2463 | 0.7023 | 0.1501 | 0.2438 |
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+ | No log | 4.0 | 272 | 0.2131 | 0.7077 | 0.1542 | 0.2491 |
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+ | No log | 5.0 | 340 | 0.1964 | 0.7246 | 0.1572 | 0.254 |
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+ | No log | 6.0 | 408 | 0.1819 | 0.7362 | 0.1582 | 0.2563 |
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+ | No log | 7.0 | 476 | 0.1662 | 0.729 | 0.1588 | 0.2565 |
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+ | 0.4062 | 8.0 | 544 | 0.1628 | 0.7666 | 0.166 | 0.2683 |
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+ | 0.4062 | 9.0 | 612 | 0.1565 | 0.7486 | 0.1625 | 0.2625 |
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+ | 0.4062 | 10.0 | 680 | 0.1522 | 0.756 | 0.1652 | 0.2667 |
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+ | 0.4062 | 11.0 | 748 | 0.1436 | 0.741 | 0.1584 | 0.2574 |
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+ | 0.4062 | 12.0 | 816 | 0.1450 | 0.7478 | 0.1624 | 0.2627 |
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+ | 0.4062 | 13.0 | 884 | 0.1369 | 0.7563 | 0.1672 | 0.2696 |
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+ | 0.4062 | 14.0 | 952 | 0.1356 | 0.7508 | 0.163 | 0.2638 |
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+ | 0.128 | 15.0 | 1020 | 0.1318 | 0.7606 | 0.1645 | 0.2669 |
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+ | 0.128 | 16.0 | 1088 | 0.1325 | 0.7805 | 0.1715 | 0.2768 |
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+ | 0.128 | 17.0 | 1156 | 0.1273 | 0.7742 | 0.1688 | 0.2727 |
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+ | 0.128 | 18.0 | 1224 | 0.1265 | 0.7842 | 0.1716 | 0.2771 |
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+ | 0.128 | 19.0 | 1292 | 0.1264 | 0.7787 | 0.1696 | 0.2741 |
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+ | 0.128 | 20.0 | 1360 | 0.1247 | 0.7856 | 0.172 | 0.2776 |
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+ | 0.128 | 21.0 | 1428 | 0.1237 | 0.7754 | 0.1688 | 0.2734 |
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+ | 0.128 | 22.0 | 1496 | 0.1226 | 0.7835 | 0.1697 | 0.2747 |
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+ | 0.0903 | 23.0 | 1564 | 0.1225 | 0.78 | 0.1683 | 0.2725 |
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+ | 0.0903 | 24.0 | 1632 | 0.1207 | 0.7824 | 0.17 | 0.2753 |
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+ | 0.0903 | 25.0 | 1700 | 0.1208 | 0.7864 | 0.1702 | 0.2756 |
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+ | 0.0903 | 26.0 | 1768 | 0.1206 | 0.7885 | 0.1722 | 0.2783 |
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+ | 0.0903 | 27.0 | 1836 | 0.1189 | 0.788 | 0.1719 | 0.2778 |
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+ | 0.0903 | 28.0 | 1904 | 0.1199 | 0.8001 | 0.1742 | 0.2814 |
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+ | 0.0903 | 29.0 | 1972 | 0.1195 | 0.7957 | 0.1732 | 0.2797 |
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+ | 0.0753 | 30.0 | 2040 | 0.1192 | 0.7957 | 0.1732 | 0.2797 |
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  ### Framework versions