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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: 0.0747
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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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@@ -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 | 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
 
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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: 0.0733
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+ - Rouge2 Precision: 0.9124
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+ - Rouge2 Recall: 0.405
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+ - Rouge2 Fmeasure: 0.5291
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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 | 1.9724 | 0.0931 | 0.0257 | 0.0386 |
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+ | No log | 2.0 | 22 | 1.2952 | 0.0923 | 0.0261 | 0.0386 |
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+ | No log | 3.0 | 33 | 0.8639 | 0.1081 | 0.0261 | 0.0405 |
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+ | No log | 4.0 | 44 | 0.5684 | 0.2273 | 0.0945 | 0.1281 |
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+ | No log | 5.0 | 55 | 0.3793 | 0.4304 | 0.1823 | 0.2449 |
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+ | No log | 6.0 | 66 | 0.2920 | 0.6664 | 0.3135 | 0.401 |
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+ | No log | 7.0 | 77 | 0.2351 | 0.7222 | 0.3114 | 0.4113 |
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+ | No log | 8.0 | 88 | 0.2055 | 0.7373 | 0.3141 | 0.4147 |
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+ | No log | 9.0 | 99 | 0.1787 | 0.7308 | 0.3023 | 0.4055 |
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+ | No log | 10.0 | 110 | 0.1540 | 0.7755 | 0.3297 | 0.4373 |
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+ | No log | 11.0 | 121 | 0.1406 | 0.7661 | 0.3217 | 0.4269 |
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+ | No log | 12.0 | 132 | 0.1299 | 0.8462 | 0.3729 | 0.488 |
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+ | No log | 13.0 | 143 | 0.1172 | 0.8169 | 0.353 | 0.4671 |
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+ | No log | 14.0 | 154 | 0.1133 | 0.8509 | 0.382 | 0.4972 |
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+ | No log | 15.0 | 165 | 0.1049 | 0.8509 | 0.382 | 0.4972 |
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+ | No log | 16.0 | 176 | 0.0988 | 0.8234 | 0.3471 | 0.462 |
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+ | No log | 17.0 | 187 | 0.0921 | 0.8696 | 0.3852 | 0.5048 |
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+ | No log | 18.0 | 198 | 0.0877 | 0.8575 | 0.3676 | 0.488 |
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+ | No log | 19.0 | 209 | 0.0878 | 0.8575 | 0.3648 | 0.485 |
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+ | No log | 20.0 | 220 | 0.0849 | 0.8575 | 0.3648 | 0.485 |
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+ | No log | 21.0 | 231 | 0.0806 | 0.8784 | 0.3785 | 0.499 |
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+ | No log | 22.0 | 242 | 0.0791 | 0.9217 | 0.4101 | 0.5348 |
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+ | No log | 23.0 | 253 | 0.0794 | 0.8959 | 0.3901 | 0.5133 |
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+ | No log | 24.0 | 264 | 0.0773 | 0.9198 | 0.412 | 0.537 |
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+ | No log | 25.0 | 275 | 0.0744 | 0.9217 | 0.4101 | 0.5348 |
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+ | No log | 26.0 | 286 | 0.0735 | 0.9217 | 0.4101 | 0.5348 |
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+ | No log | 27.0 | 297 | 0.0742 | 0.9257 | 0.4136 | 0.5394 |
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+ | No log | 28.0 | 308 | 0.0740 | 0.9124 | 0.405 | 0.5291 |
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+ | No log | 29.0 | 319 | 0.0734 | 0.9124 | 0.405 | 0.5291 |
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+ | No log | 30.0 | 330 | 0.0733 | 0.9124 | 0.405 | 0.5291 |
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  ### Framework versions