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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: 0.2640
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- - Rouge2 Precision: 0.8439
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- - Rouge2 Recall: 0.3803
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- - Rouge2 Fmeasure: 0.5034
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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 | 2.7587 | 0.0976 | 0.0301 | 0.0443 |
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- | No log | 2.0 | 22 | 2.0056 | 0.0971 | 0.0279 | 0.0413 |
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- | No log | 3.0 | 33 | 1.4456 | 0.1043 | 0.0344 | 0.05 |
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- | No log | 4.0 | 44 | 1.0317 | 0.1048 | 0.033 | 0.0474 |
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- | No log | 5.0 | 55 | 0.7603 | 0.2774 | 0.1307 | 0.1726 |
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- | No log | 6.0 | 66 | 0.5722 | 0.7082 | 0.3512 | 0.4539 |
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- | No log | 7.0 | 77 | 0.4751 | 0.684 | 0.3342 | 0.4333 |
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- | No log | 8.0 | 88 | 0.4253 | 0.7224 | 0.3426 | 0.4447 |
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- | No log | 9.0 | 99 | 0.3805 | 0.7327 | 0.3183 | 0.4275 |
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- | No log | 10.0 | 110 | 0.3562 | 0.7335 | 0.3227 | 0.4306 |
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- | No log | 11.0 | 121 | 0.3275 | 0.7881 | 0.3544 | 0.469 |
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- | No log | 12.0 | 132 | 0.3133 | 0.836 | 0.3797 | 0.5027 |
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- | No log | 13.0 | 143 | 0.2996 | 0.8379 | 0.3803 | 0.5031 |
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- | No log | 14.0 | 154 | 0.2903 | 0.8265 | 0.3728 | 0.4927 |
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- | No log | 15.0 | 165 | 0.2867 | 0.8379 | 0.3803 | 0.5031 |
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- | No log | 16.0 | 176 | 0.2786 | 0.8379 | 0.3803 | 0.5031 |
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- | No log | 17.0 | 187 | 0.2711 | 0.8379 | 0.3803 | 0.5031 |
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- | No log | 18.0 | 198 | 0.2673 | 0.8379 | 0.3803 | 0.5031 |
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- | No log | 19.0 | 209 | 0.2643 | 0.8439 | 0.3803 | 0.5034 |
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- | No log | 20.0 | 220 | 0.2640 | 0.8439 | 0.3803 | 0.5034 |
 
 
 
 
 
 
 
 
 
 
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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: 0.1189
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+ - Rouge2 Precision: 0.9177
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+ - Rouge2 Recall: 0.4311
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+ - Rouge2 Fmeasure: 0.5617
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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 | 0.1481 | 0.8982 | 0.4224 | 0.5515 |
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+ | No log | 2.0 | 22 | 0.1409 | 0.939 | 0.4393 | 0.5736 |
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+ | No log | 3.0 | 33 | 0.1352 | 0.939 | 0.4393 | 0.5736 |
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+ | No log | 4.0 | 44 | 0.1279 | 0.9294 | 0.4353 | 0.5679 |
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+ | No log | 5.0 | 55 | 0.1244 | 0.9192 | 0.4307 | 0.5633 |
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+ | No log | 6.0 | 66 | 0.1294 | 0.9331 | 0.4379 | 0.5716 |
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+ | No log | 7.0 | 77 | 0.1358 | 0.939 | 0.4393 | 0.5736 |
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+ | No log | 8.0 | 88 | 0.1304 | 0.9331 | 0.4379 | 0.5716 |
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+ | No log | 9.0 | 99 | 0.1312 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 10.0 | 110 | 0.1291 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 11.0 | 121 | 0.1319 | 0.9138 | 0.4311 | 0.5616 |
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+ | No log | 12.0 | 132 | 0.1264 | 0.9113 | 0.4273 | 0.5586 |
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+ | No log | 13.0 | 143 | 0.1273 | 0.907 | 0.4246 | 0.555 |
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+ | No log | 14.0 | 154 | 0.1181 | 0.9113 | 0.4273 | 0.5586 |
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+ | No log | 15.0 | 165 | 0.1196 | 0.9113 | 0.4273 | 0.5586 |
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+ | No log | 16.0 | 176 | 0.1168 | 0.907 | 0.4246 | 0.555 |
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+ | No log | 17.0 | 187 | 0.1190 | 0.9232 | 0.4348 | 0.5672 |
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+ | No log | 18.0 | 198 | 0.1162 | 0.9113 | 0.4273 | 0.5586 |
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+ | No log | 19.0 | 209 | 0.1160 | 0.907 | 0.4246 | 0.555 |
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+ | No log | 20.0 | 220 | 0.1188 | 0.9113 | 0.4246 | 0.5554 |
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+ | No log | 21.0 | 231 | 0.1200 | 0.9113 | 0.4246 | 0.5554 |
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+ | No log | 22.0 | 242 | 0.1226 | 0.9113 | 0.4246 | 0.5554 |
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+ | No log | 23.0 | 253 | 0.1235 | 0.9155 | 0.4273 | 0.5592 |
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+ | No log | 24.0 | 264 | 0.1206 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 25.0 | 275 | 0.1189 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 26.0 | 286 | 0.1197 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 27.0 | 297 | 0.1202 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 28.0 | 308 | 0.1199 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 29.0 | 319 | 0.1192 | 0.9177 | 0.4311 | 0.5617 |
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+ | No log | 30.0 | 330 | 0.1189 | 0.9177 | 0.4311 | 0.5617 |
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  ### Framework versions