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t5-text2sql

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t5
text2text-generation
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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: 0.3843
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- - Rouge2 Precision: 0.8546
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- - Rouge2 Recall: 0.3305
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- - Rouge2 Fmeasure: 0.4564
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  ## Model description
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@@ -42,44 +42,52 @@ 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: 32
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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 | 2.6539 | 0.072 | 0.0232 | 0.0349 |
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- | No log | 2.0 | 22 | 1.8002 | 0.0465 | 0.0131 | 0.02 |
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- | No log | 3.0 | 33 | 1.2897 | 0.1874 | 0.0596 | 0.0859 |
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- | No log | 4.0 | 44 | 0.8970 | 0.5344 | 0.232 | 0.3114 |
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- | No log | 5.0 | 55 | 0.7295 | 0.7108 | 0.3043 | 0.4135 |
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- | No log | 6.0 | 66 | 0.6333 | 0.763 | 0.2887 | 0.4042 |
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- | No log | 7.0 | 77 | 0.5959 | 0.7765 | 0.2992 | 0.4134 |
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- | No log | 8.0 | 88 | 0.5394 | 0.7621 | 0.2849 | 0.3994 |
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- | No log | 9.0 | 99 | 0.5125 | 0.7692 | 0.2915 | 0.4045 |
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- | No log | 10.0 | 110 | 0.4889 | 0.8046 | 0.3095 | 0.4295 |
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- | No log | 11.0 | 121 | 0.4743 | 0.8536 | 0.3268 | 0.4525 |
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- | No log | 12.0 | 132 | 0.4631 | 0.8405 | 0.3233 | 0.4467 |
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- | No log | 13.0 | 143 | 0.4494 | 0.8611 | 0.3307 | 0.4572 |
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- | No log | 14.0 | 154 | 0.4357 | 0.8687 | 0.3386 | 0.4669 |
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- | No log | 15.0 | 165 | 0.4319 | 0.8494 | 0.3271 | 0.4524 |
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- | No log | 16.0 | 176 | 0.4243 | 0.8503 | 0.3271 | 0.4519 |
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- | No log | 17.0 | 187 | 0.4175 | 0.8647 | 0.3318 | 0.4592 |
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- | No log | 18.0 | 198 | 0.4145 | 0.8766 | 0.3375 | 0.4664 |
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- | No log | 19.0 | 209 | 0.4073 | 0.8727 | 0.3348 | 0.4632 |
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- | No log | 20.0 | 220 | 0.4039 | 0.8766 | 0.3375 | 0.4664 |
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- | No log | 21.0 | 231 | 0.4002 | 0.8528 | 0.3291 | 0.4546 |
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- | No log | 22.0 | 242 | 0.3939 | 0.8488 | 0.3278 | 0.4524 |
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- | No log | 23.0 | 253 | 0.3952 | 0.8492 | 0.3283 | 0.4538 |
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- | No log | 24.0 | 264 | 0.3898 | 0.8586 | 0.3313 | 0.4588 |
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- | No log | 25.0 | 275 | 0.3869 | 0.8586 | 0.3313 | 0.4588 |
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- | No log | 26.0 | 286 | 0.3883 | 0.8532 | 0.3305 | 0.4566 |
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- | No log | 27.0 | 297 | 0.3839 | 0.8586 | 0.3313 | 0.4588 |
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- | No log | 28.0 | 308 | 0.3831 | 0.8586 | 0.3313 | 0.4588 |
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- | No log | 29.0 | 319 | 0.3845 | 0.8546 | 0.3305 | 0.4564 |
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- | No log | 30.0 | 330 | 0.3850 | 0.8546 | 0.3305 | 0.4564 |
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- | No log | 31.0 | 341 | 0.3843 | 0.8546 | 0.3305 | 0.4564 |
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- | No log | 32.0 | 352 | 0.3843 | 0.8546 | 0.3305 | 0.4564 |
 
 
 
 
 
 
 
 
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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: 0.3787
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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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  - 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: 40
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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 | 2.6398 | 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