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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: 0.9499
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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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@@ -48,41 +48,41 @@ 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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- - Transformers 4.21.2
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  - Pytorch 1.12.1+cu113
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- - Datasets 2.4.0
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- - Tokenizers 0.12.1
 
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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: 0.0739
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+ - Rouge2 Precision: 0.9355
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+ - Rouge2 Recall: 0.3211
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+ - Rouge2 Fmeasure: 0.455
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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 | 2.1518 | 0.0531 | 0.0137 | 0.0212 |
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+ | No log | 2.0 | 22 | 1.3941 | 0.0642 | 0.0183 | 0.0271 |
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+ | No log | 3.0 | 33 | 0.9268 | 0.0619 | 0.0183 | 0.027 |
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+ | No log | 4.0 | 44 | 0.5761 | 0.0424 | 0.015 | 0.0213 |
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+ | No log | 5.0 | 55 | 0.3922 | 0.4683 | 0.1715 | 0.2361 |
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+ | No log | 6.0 | 66 | 0.2948 | 0.6561 | 0.238 | 0.326 |
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+ | No log | 7.0 | 77 | 0.2294 | 0.8072 | 0.2847 | 0.3958 |
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+ | No log | 8.0 | 88 | 0.1959 | 0.7839 | 0.2851 | 0.3965 |
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+ | No log | 9.0 | 99 | 0.1674 | 0.8266 | 0.2916 | 0.4074 |
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+ | No log | 10.0 | 110 | 0.1488 | 0.8717 | 0.3057 | 0.428 |
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+ | No log | 11.0 | 121 | 0.1328 | 0.8851 | 0.3178 | 0.4412 |
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+ | No log | 12.0 | 132 | 0.1205 | 0.8887 | 0.3197 | 0.4453 |
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+ | No log | 13.0 | 143 | 0.1133 | 0.8887 | 0.3197 | 0.4453 |
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+ | No log | 14.0 | 154 | 0.1054 | 0.9124 | 0.3328 | 0.4595 |
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+ | No log | 15.0 | 165 | 0.1000 | 0.9214 | 0.3352 | 0.4632 |
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+ | No log | 16.0 | 176 | 0.0964 | 0.9133 | 0.3318 | 0.4598 |
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+ | No log | 17.0 | 187 | 0.0957 | 0.9205 | 0.3325 | 0.4612 |
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+ | No log | 18.0 | 198 | 0.0883 | 0.9405 | 0.3352 | 0.4663 |
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+ | No log | 19.0 | 209 | 0.0845 | 0.9413 | 0.3336 | 0.4666 |
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+ | No log | 20.0 | 220 | 0.0825 | 0.9172 | 0.3238 | 0.4532 |
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+ | No log | 21.0 | 231 | 0.0803 | 0.9172 | 0.3238 | 0.4532 |
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+ | No log | 22.0 | 242 | 0.0788 | 0.929 | 0.3301 | 0.4617 |
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+ | No log | 23.0 | 253 | 0.0789 | 0.9463 | 0.3343 | 0.468 |
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+ | No log | 24.0 | 264 | 0.0784 | 0.9355 | 0.3211 | 0.455 |
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+ | No log | 25.0 | 275 | 0.0778 | 0.9355 | 0.3211 | 0.455 |
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+ | No log | 26.0 | 286 | 0.0767 | 0.9355 | 0.3211 | 0.455 |
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+ | No log | 27.0 | 297 | 0.0759 | 0.9355 | 0.3211 | 0.455 |
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+ | No log | 28.0 | 308 | 0.0749 | 0.9355 | 0.3211 | 0.455 |
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+ | No log | 29.0 | 319 | 0.0742 | 0.9355 | 0.3211 | 0.455 |
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+ | No log | 30.0 | 330 | 0.0739 | 0.9355 | 0.3211 | 0.455 |
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  ### Framework versions
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+ - Transformers 4.24.0
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  - Pytorch 1.12.1+cu113
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+ - Datasets 2.7.1
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+ - Tokenizers 0.13.2