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t5-text2sql

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PyTorch
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t5
text2text-generation
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: 0.2416
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- - Rouge2 Precision: 0.8462
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- - Rouge2 Recall: 0.3885
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- - Rouge2 Fmeasure: 0.5121
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  ## Model description
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@@ -42,32 +42,42 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 20
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  ### Training results
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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 | 2.7131 | 0.0949 | 0.0274 | 0.0408 |
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- | No log | 2.0 | 22 | 1.8494 | 0.1002 | 0.0344 | 0.0496 |
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- | No log | 3.0 | 33 | 1.3319 | 0.1002 | 0.0344 | 0.0496 |
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- | No log | 4.0 | 44 | 0.9292 | 0.2173 | 0.0978 | 0.1301 |
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- | No log | 5.0 | 55 | 0.6819 | 0.6437 | 0.2999 | 0.3965 |
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- | No log | 6.0 | 66 | 0.5479 | 0.7469 | 0.3684 | 0.4781 |
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- | No log | 7.0 | 77 | 0.4565 | 0.775 | 0.3583 | 0.4715 |
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- | No log | 8.0 | 88 | 0.3960 | 0.7726 | 0.3547 | 0.4683 |
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- | No log | 9.0 | 99 | 0.3681 | 0.7736 | 0.3566 | 0.4692 |
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- | No log | 10.0 | 110 | 0.3370 | 0.7372 | 0.3191 | 0.4286 |
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- | No log | 11.0 | 121 | 0.3134 | 0.758 | 0.3404 | 0.453 |
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- | No log | 12.0 | 132 | 0.2914 | 0.7934 | 0.361 | 0.4779 |
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- | No log | 13.0 | 143 | 0.2766 | 0.7888 | 0.3599 | 0.476 |
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- | No log | 14.0 | 154 | 0.2678 | 0.8269 | 0.3819 | 0.5039 |
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- | No log | 15.0 | 165 | 0.2587 | 0.8269 | 0.3819 | 0.5039 |
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- | No log | 16.0 | 176 | 0.2523 | 0.8447 | 0.3847 | 0.5084 |
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- | No log | 17.0 | 187 | 0.2471 | 0.831 | 0.3802 | 0.5011 |
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- | No log | 18.0 | 198 | 0.2440 | 0.8462 | 0.3885 | 0.5121 |
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- | No log | 19.0 | 209 | 0.2423 | 0.8462 | 0.3885 | 0.5121 |
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- | No log | 20.0 | 220 | 0.2416 | 0.8462 | 0.3885 | 0.5121 |
 
 
 
 
 
 
 
 
 
 
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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: 0.1562
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+ - Rouge2 Precision: 0.9158
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+ - Rouge2 Recall: 0.4313
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+ - Rouge2 Fmeasure: 0.5626
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 30
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  ### Training results
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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 | 2.7478 | 0.0909 | 0.0282 | 0.0413 |
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+ | No log | 2.0 | 22 | 1.9795 | 0.0967 | 0.0283 | 0.0421 |
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+ | No log | 3.0 | 33 | 1.4496 | 0.1016 | 0.0283 | 0.0431 |
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+ | No log | 4.0 | 44 | 0.9816 | 0.0874 | 0.0275 | 0.0409 |
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+ | No log | 5.0 | 55 | 0.7077 | 0.3404 | 0.1332 | 0.185 |
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+ | No log | 6.0 | 66 | 0.5237 | 0.6676 | 0.332 | 0.4275 |
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+ | No log | 7.0 | 77 | 0.4239 | 0.7219 | 0.3213 | 0.4279 |
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+ | No log | 8.0 | 88 | 0.3717 | 0.8036 | 0.3653 | 0.4815 |
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+ | No log | 9.0 | 99 | 0.3335 | 0.7738 | 0.3451 | 0.4581 |
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+ | No log | 10.0 | 110 | 0.3048 | 0.7887 | 0.3487 | 0.4657 |
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+ | No log | 11.0 | 121 | 0.2738 | 0.8186 | 0.369 | 0.4878 |
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+ | No log | 12.0 | 132 | 0.2596 | 0.8444 | 0.3903 | 0.513 |
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+ | No log | 13.0 | 143 | 0.2432 | 0.8215 | 0.3731 | 0.4934 |
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+ | No log | 14.0 | 154 | 0.2356 | 0.8514 | 0.3903 | 0.5128 |
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+ | No log | 15.0 | 165 | 0.2272 | 0.8661 | 0.3932 | 0.5178 |
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+ | No log | 16.0 | 176 | 0.2077 | 0.8754 | 0.3956 | 0.5216 |
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+ | No log | 17.0 | 187 | 0.1991 | 0.8757 | 0.3963 | 0.5229 |
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+ | No log | 18.0 | 198 | 0.1928 | 0.8893 | 0.4077 | 0.5353 |
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+ | No log | 19.0 | 209 | 0.1828 | 0.8893 | 0.4077 | 0.5353 |
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+ | No log | 20.0 | 220 | 0.1820 | 0.8721 | 0.3945 | 0.5203 |
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+ | No log | 21.0 | 231 | 0.1786 | 0.8927 | 0.4096 | 0.5385 |
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+ | No log | 22.0 | 242 | 0.1761 | 0.9064 | 0.4212 | 0.5512 |
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+ | No log | 23.0 | 253 | 0.1710 | 0.9064 | 0.4212 | 0.5512 |
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+ | No log | 24.0 | 264 | 0.1655 | 0.9158 | 0.4313 | 0.5626 |
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+ | No log | 25.0 | 275 | 0.1622 | 0.9158 | 0.4313 | 0.5626 |
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+ | No log | 26.0 | 286 | 0.1597 | 0.9158 | 0.4313 | 0.5626 |
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+ | No log | 27.0 | 297 | 0.1579 | 0.9158 | 0.4313 | 0.5626 |
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+ | No log | 28.0 | 308 | 0.1565 | 0.9158 | 0.4313 | 0.5626 |
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+ | No log | 29.0 | 319 | 0.1564 | 0.9158 | 0.4313 | 0.5626 |
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+ | No log | 30.0 | 330 | 0.1562 | 0.9158 | 0.4313 | 0.5626 |
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  ### Framework versions