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t5-text2sql

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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: 0.3787
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  - Rouge2 Precision: 0.8135
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- - Rouge2 Recall: 0.3015
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- - Rouge2 Fmeasure: 0.4231
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  ## Model description
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@@ -48,46 +48,46 @@ 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 | 2.6398 | 0.0707 | 0.0228 | 0.0344 |
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- | No log | 2.0 | 22 | 1.7754 | 0.0509 | 0.0137 | 0.0208 |
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- | No log | 3.0 | 33 | 1.2567 | 0.1857 | 0.067 | 0.0925 |
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- | No log | 4.0 | 44 | 0.8637 | 0.5631 | 0.2527 | 0.3375 |
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- | No log | 5.0 | 55 | 0.7057 | 0.7095 | 0.3029 | 0.4124 |
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- | No log | 6.0 | 66 | 0.6357 | 0.7581 | 0.2958 | 0.4062 |
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- | No log | 7.0 | 77 | 0.5939 | 0.7858 | 0.3051 | 0.4201 |
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- | No log | 8.0 | 88 | 0.5313 | 0.7949 | 0.3027 | 0.4199 |
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- | No log | 9.0 | 99 | 0.5116 | 0.8056 | 0.3089 | 0.4284 |
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- | No log | 10.0 | 110 | 0.4812 | 0.8086 | 0.3117 | 0.4322 |
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- | No log | 11.0 | 121 | 0.4683 | 0.8386 | 0.3252 | 0.446 |
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- | No log | 12.0 | 132 | 0.4492 | 0.8424 | 0.3271 | 0.4495 |
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- | No log | 13.0 | 143 | 0.4398 | 0.8588 | 0.3321 | 0.4579 |
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- | No log | 14.0 | 154 | 0.4276 | 0.8588 | 0.3321 | 0.4579 |
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- | No log | 15.0 | 165 | 0.4276 | 0.873 | 0.3375 | 0.4661 |
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- | No log | 16.0 | 176 | 0.4225 | 0.8683 | 0.3347 | 0.4627 |
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- | No log | 17.0 | 187 | 0.4080 | 0.8764 | 0.3378 | 0.4664 |
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- | No log | 18.0 | 198 | 0.4046 | 0.8727 | 0.3365 | 0.4638 |
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- | No log | 19.0 | 209 | 0.4005 | 0.8687 | 0.3366 | 0.4638 |
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- | No log | 20.0 | 220 | 0.3976 | 0.8651 | 0.3348 | 0.4626 |
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- | No log | 21.0 | 231 | 0.3937 | 0.8434 | 0.3271 | 0.4514 |
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- | No log | 22.0 | 242 | 0.3884 | 0.8434 | 0.3271 | 0.4514 |
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- | No log | 23.0 | 253 | 0.3888 | 0.8153 | 0.2992 | 0.4221 |
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- | No log | 24.0 | 264 | 0.3833 | 0.8059 | 0.2985 | 0.4195 |
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- | No log | 25.0 | 275 | 0.3808 | 0.8229 | 0.3038 | 0.4272 |
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- | No log | 26.0 | 286 | 0.3857 | 0.8137 | 0.2992 | 0.4218 |
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- | No log | 27.0 | 297 | 0.3780 | 0.8571 | 0.3339 | 0.4589 |
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- | No log | 28.0 | 308 | 0.3813 | 0.8413 | 0.3093 | 0.4369 |
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- | No log | 29.0 | 319 | 0.3853 | 0.869 | 0.3357 | 0.4638 |
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- | No log | 30.0 | 330 | 0.3808 | 0.8373 | 0.3081 | 0.4348 |
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- | No log | 31.0 | 341 | 0.3777 | 0.8149 | 0.2957 | 0.4183 |
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- | No log | 32.0 | 352 | 0.3747 | 0.8149 | 0.2957 | 0.4183 |
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- | No log | 33.0 | 363 | 0.3734 | 0.8452 | 0.3107 | 0.439 |
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- | No log | 34.0 | 374 | 0.3767 | 0.7971 | 0.2963 | 0.4151 |
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- | No log | 35.0 | 385 | 0.3793 | 0.8135 | 0.3015 | 0.4231 |
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- | No log | 36.0 | 396 | 0.3804 | 0.8135 | 0.3015 | 0.4231 |
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- | No log | 37.0 | 407 | 0.3793 | 0.8135 | 0.3015 | 0.4231 |
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- | No log | 38.0 | 418 | 0.3778 | 0.8135 | 0.3015 | 0.4231 |
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- | No log | 39.0 | 429 | 0.3785 | 0.8135 | 0.3015 | 0.4231 |
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- | No log | 40.0 | 440 | 0.3787 | 0.8135 | 0.3015 | 0.4231 |
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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: 0.4977
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  - Rouge2 Precision: 0.8135
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+ - Rouge2 Recall: 0.3117
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+ - Rouge2 Fmeasure: 0.4298
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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 | 2.8516 | 0.0306 | 0.0054 | 0.0091 |
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+ | No log | 2.0 | 22 | 1.9542 | 0.0391 | 0.0119 | 0.0173 |
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+ | No log | 3.0 | 33 | 1.4651 | 0.2077 | 0.0735 | 0.1042 |
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+ | No log | 4.0 | 44 | 1.0618 | 0.5873 | 0.2521 | 0.3435 |
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+ | No log | 5.0 | 55 | 0.8918 | 0.7148 | 0.3032 | 0.4136 |
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+ | No log | 6.0 | 66 | 0.7871 | 0.7623 | 0.2922 | 0.4067 |
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+ | No log | 7.0 | 77 | 0.7451 | 0.7756 | 0.286 | 0.4002 |
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+ | No log | 8.0 | 88 | 0.6902 | 0.7734 | 0.2876 | 0.4022 |
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+ | No log | 9.0 | 99 | 0.6638 | 0.7913 | 0.295 | 0.4125 |
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+ | No log | 10.0 | 110 | 0.6434 | 0.7857 | 0.2923 | 0.4101 |
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+ | No log | 11.0 | 121 | 0.6248 | 0.8016 | 0.309 | 0.4262 |
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+ | No log | 12.0 | 132 | 0.6035 | 0.7976 | 0.3003 | 0.42 |
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+ | No log | 13.0 | 143 | 0.5936 | 0.8294 | 0.3186 | 0.4405 |
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+ | No log | 14.0 | 154 | 0.5608 | 0.8333 | 0.3204 | 0.4427 |
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+ | No log | 15.0 | 165 | 0.5717 | 0.8333 | 0.3204 | 0.4427 |
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+ | No log | 16.0 | 176 | 0.5615 | 0.8292 | 0.3183 | 0.4404 |
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+ | No log | 17.0 | 187 | 0.5550 | 0.8274 | 0.3175 | 0.4394 |
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+ | No log | 18.0 | 198 | 0.5473 | 0.8254 | 0.3176 | 0.4387 |
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+ | No log | 19.0 | 209 | 0.5422 | 0.8333 | 0.3192 | 0.441 |
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+ | No log | 20.0 | 220 | 0.5335 | 0.8373 | 0.3208 | 0.4429 |
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+ | No log | 21.0 | 231 | 0.5276 | 0.8294 | 0.3191 | 0.4409 |
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+ | No log | 22.0 | 242 | 0.5257 | 0.8611 | 0.3291 | 0.4558 |
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+ | No log | 23.0 | 253 | 0.5339 | 0.8387 | 0.3198 | 0.4433 |
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+ | No log | 24.0 | 264 | 0.5302 | 0.8492 | 0.325 | 0.4495 |
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+ | No log | 25.0 | 275 | 0.5187 | 0.8562 | 0.3284 | 0.4527 |
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+ | No log | 26.0 | 286 | 0.5208 | 0.8562 | 0.3284 | 0.4527 |
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+ | No log | 27.0 | 297 | 0.5170 | 0.8611 | 0.3295 | 0.4555 |
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+ | No log | 28.0 | 308 | 0.5095 | 0.8671 | 0.3318 | 0.4604 |
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+ | No log | 29.0 | 319 | 0.5128 | 0.8651 | 0.3307 | 0.4584 |
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+ | No log | 30.0 | 330 | 0.5074 | 0.8175 | 0.3145 | 0.4334 |
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+ | No log | 31.0 | 341 | 0.4990 | 0.8175 | 0.3145 | 0.4334 |
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+ | No log | 32.0 | 352 | 0.4985 | 0.8175 | 0.3145 | 0.4334 |
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+ | No log | 33.0 | 363 | 0.5006 | 0.8229 | 0.316 | 0.4359 |
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+ | No log | 34.0 | 374 | 0.4975 | 0.869 | 0.3318 | 0.4606 |
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+ | No log | 35.0 | 385 | 0.4987 | 0.8591 | 0.3294 | 0.4564 |
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+ | No log | 36.0 | 396 | 0.4968 | 0.8591 | 0.3294 | 0.4564 |
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+ | No log | 37.0 | 407 | 0.4960 | 0.8591 | 0.3283 | 0.455 |
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+ | No log | 38.0 | 418 | 0.4965 | 0.8353 | 0.3192 | 0.4425 |
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+ | No log | 39.0 | 429 | 0.4978 | 0.8135 | 0.3117 | 0.4298 |
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+ | No log | 40.0 | 440 | 0.4977 | 0.8135 | 0.3117 | 0.4298 |
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  ### Framework versions