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t5-text2sql_v1

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

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@@ -14,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.1265
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- - Rouge2 Precision: 0.7737
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- - Rouge2 Recall: 0.1686
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- - Rouge2 Fmeasure: 0.2725
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  ## Model description
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@@ -48,36 +48,36 @@ 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 | 68 | 0.7014 | 0.5788 | 0.1438 | 0.2267 |
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- | No log | 2.0 | 136 | 0.3643 | 0.6424 | 0.1388 | 0.2254 |
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- | No log | 3.0 | 204 | 0.2811 | 0.6499 | 0.1433 | 0.2319 |
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- | No log | 4.0 | 272 | 0.2344 | 0.6552 | 0.1401 | 0.2276 |
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- | No log | 5.0 | 340 | 0.2165 | 0.7083 | 0.1534 | 0.2485 |
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- | No log | 6.0 | 408 | 0.1950 | 0.6835 | 0.1498 | 0.2421 |
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- | No log | 7.0 | 476 | 0.1801 | 0.7303 | 0.1584 | 0.2562 |
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- | 0.5608 | 8.0 | 544 | 0.1784 | 0.7246 | 0.1565 | 0.2537 |
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- | 0.5608 | 9.0 | 612 | 0.1670 | 0.7308 | 0.1575 | 0.2552 |
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- | 0.5608 | 10.0 | 680 | 0.1619 | 0.7388 | 0.1587 | 0.2572 |
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- | 0.5608 | 11.0 | 748 | 0.1545 | 0.724 | 0.1551 | 0.2518 |
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- | 0.5608 | 12.0 | 816 | 0.1554 | 0.7271 | 0.1563 | 0.2534 |
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- | 0.5608 | 13.0 | 884 | 0.1472 | 0.7404 | 0.1624 | 0.2624 |
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- | 0.5608 | 14.0 | 952 | 0.1472 | 0.7508 | 0.1613 | 0.2616 |
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- | 0.1384 | 15.0 | 1020 | 0.1429 | 0.765 | 0.1651 | 0.2679 |
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- | 0.1384 | 16.0 | 1088 | 0.1416 | 0.7564 | 0.1626 | 0.2636 |
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- | 0.1384 | 17.0 | 1156 | 0.1365 | 0.7737 | 0.1653 | 0.2684 |
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- | 0.1384 | 18.0 | 1224 | 0.1344 | 0.7594 | 0.1639 | 0.2656 |
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- | 0.1384 | 19.0 | 1292 | 0.1356 | 0.7618 | 0.1667 | 0.2693 |
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- | 0.1384 | 20.0 | 1360 | 0.1339 | 0.7691 | 0.1673 | 0.2705 |
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- | 0.1384 | 21.0 | 1428 | 0.1335 | 0.7624 | 0.1646 | 0.267 |
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- | 0.1384 | 22.0 | 1496 | 0.1325 | 0.7691 | 0.1664 | 0.2694 |
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- | 0.0974 | 23.0 | 1564 | 0.1297 | 0.7612 | 0.1657 | 0.2679 |
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- | 0.0974 | 24.0 | 1632 | 0.1296 | 0.7628 | 0.1663 | 0.2691 |
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- | 0.0974 | 25.0 | 1700 | 0.1288 | 0.7601 | 0.1648 | 0.2667 |
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- | 0.0974 | 26.0 | 1768 | 0.1284 | 0.7633 | 0.1653 | 0.2679 |
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- | 0.0974 | 27.0 | 1836 | 0.1272 | 0.7684 | 0.1663 | 0.2696 |
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- | 0.0974 | 28.0 | 1904 | 0.1272 | 0.7729 | 0.1683 | 0.2722 |
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- | 0.0974 | 29.0 | 1972 | 0.1265 | 0.7765 | 0.169 | 0.2732 |
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- | 0.081 | 30.0 | 2040 | 0.1265 | 0.7737 | 0.1686 | 0.2725 |
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  ### Framework versions
 
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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: 0.9484
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+ - Rouge2 Recall: 0.326
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+ - Rouge2 Fmeasure: 0.4583
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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 | 11 | 2.1363 | 0.0475 | 0.0107 | 0.0173 |
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+ | No log | 2.0 | 22 | 1.3415 | 0.0484 | 0.0107 | 0.0173 |
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+ | No log | 3.0 | 33 | 0.8590 | 0.0445 | 0.0119 | 0.0182 |
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+ | No log | 4.0 | 44 | 0.5496 | 0.2166 | 0.0839 | 0.1172 |
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+ | No log | 5.0 | 55 | 0.3879 | 0.4392 | 0.1919 | 0.2518 |
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+ | No log | 6.0 | 66 | 0.2915 | 0.721 | 0.2583 | 0.358 |
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+ | No log | 7.0 | 77 | 0.2325 | 0.7907 | 0.2682 | 0.3822 |
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+ | No log | 8.0 | 88 | 0.1910 | 0.8413 | 0.2882 | 0.4065 |
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+ | No log | 9.0 | 99 | 0.1734 | 0.8407 | 0.2957 | 0.4122 |
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+ | No log | 10.0 | 110 | 0.1453 | 0.8895 | 0.3207 | 0.4452 |
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+ | No log | 11.0 | 121 | 0.1276 | 0.873 | 0.3112 | 0.4318 |
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+ | No log | 12.0 | 132 | 0.1236 | 0.8487 | 0.3035 | 0.4231 |
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+ | No log | 13.0 | 143 | 0.1173 | 0.8374 | 0.3013 | 0.4186 |
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+ | No log | 14.0 | 154 | 0.1085 | 0.8929 | 0.3129 | 0.4386 |
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+ | No log | 15.0 | 165 | 0.1001 | 0.9154 | 0.32 | 0.4496 |
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+ | No log | 16.0 | 176 | 0.0971 | 0.8843 | 0.3153 | 0.4418 |
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+ | No log | 17.0 | 187 | 0.0931 | 0.9082 | 0.3249 | 0.4521 |
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+ | No log | 18.0 | 198 | 0.0870 | 0.9048 | 0.3172 | 0.4442 |
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+ | No log | 19.0 | 209 | 0.0838 | 0.9295 | 0.3215 | 0.4524 |
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+ | No log | 20.0 | 220 | 0.0842 | 0.9524 | 0.3301 | 0.4632 |
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+ | No log | 21.0 | 231 | 0.0824 | 0.9524 | 0.3301 | 0.4632 |
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+ | No log | 22.0 | 242 | 0.0801 | 0.9524 | 0.3286 | 0.4618 |
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+ | No log | 23.0 | 253 | 0.0789 | 0.9304 | 0.3192 | 0.4483 |
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+ | No log | 24.0 | 264 | 0.0778 | 0.9304 | 0.3192 | 0.4483 |
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+ | No log | 25.0 | 275 | 0.0768 | 0.9304 | 0.3178 | 0.4467 |
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+ | No log | 26.0 | 286 | 0.0762 | 0.9341 | 0.3205 | 0.4512 |
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+ | No log | 27.0 | 297 | 0.0755 | 0.9484 | 0.326 | 0.4583 |
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+ | No log | 28.0 | 308 | 0.0752 | 0.9484 | 0.326 | 0.4583 |
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+ | No log | 29.0 | 319 | 0.0749 | 0.9484 | 0.326 | 0.4583 |
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+ | No log | 30.0 | 330 | 0.0747 | 0.9484 | 0.326 | 0.4583 |
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  ### Framework versions