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mousaazari
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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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@@ -15,9 +15,9 @@ 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: 0.0733
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- - Rouge2 Precision: 0.9124
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- - Rouge2 Recall: 0.405
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- - Rouge2 Fmeasure: 0.5291
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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 | 1.9724 | 0.0931 | 0.0257 | 0.0386 |
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- | No log | 2.0 | 22 | 1.2952 | 0.0923 | 0.0261 | 0.0386 |
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- | No log | 3.0 | 33 | 0.8639 | 0.1081 | 0.0261 | 0.0405 |
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- | No log | 4.0 | 44 | 0.5684 | 0.2273 | 0.0945 | 0.1281 |
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- | No log | 5.0 | 55 | 0.3793 | 0.4304 | 0.1823 | 0.2449 |
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- | No log | 6.0 | 66 | 0.2920 | 0.6664 | 0.3135 | 0.401 |
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- | No log | 7.0 | 77 | 0.2351 | 0.7222 | 0.3114 | 0.4113 |
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- | No log | 8.0 | 88 | 0.2055 | 0.7373 | 0.3141 | 0.4147 |
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- | No log | 9.0 | 99 | 0.1787 | 0.7308 | 0.3023 | 0.4055 |
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- | No log | 10.0 | 110 | 0.1540 | 0.7755 | 0.3297 | 0.4373 |
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- | No log | 11.0 | 121 | 0.1406 | 0.7661 | 0.3217 | 0.4269 |
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- | No log | 12.0 | 132 | 0.1299 | 0.8462 | 0.3729 | 0.488 |
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- | No log | 13.0 | 143 | 0.1172 | 0.8169 | 0.353 | 0.4671 |
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- | No log | 14.0 | 154 | 0.1133 | 0.8509 | 0.382 | 0.4972 |
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- | No log | 15.0 | 165 | 0.1049 | 0.8509 | 0.382 | 0.4972 |
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- | No log | 16.0 | 176 | 0.0988 | 0.8234 | 0.3471 | 0.462 |
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- | No log | 17.0 | 187 | 0.0921 | 0.8696 | 0.3852 | 0.5048 |
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- | No log | 18.0 | 198 | 0.0877 | 0.8575 | 0.3676 | 0.488 |
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- | No log | 19.0 | 209 | 0.0878 | 0.8575 | 0.3648 | 0.485 |
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- | No log | 20.0 | 220 | 0.0849 | 0.8575 | 0.3648 | 0.485 |
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- | No log | 21.0 | 231 | 0.0806 | 0.8784 | 0.3785 | 0.499 |
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- | No log | 22.0 | 242 | 0.0791 | 0.9217 | 0.4101 | 0.5348 |
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- | No log | 23.0 | 253 | 0.0794 | 0.8959 | 0.3901 | 0.5133 |
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- | No log | 24.0 | 264 | 0.0773 | 0.9198 | 0.412 | 0.537 |
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- | No log | 25.0 | 275 | 0.0744 | 0.9217 | 0.4101 | 0.5348 |
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- | No log | 26.0 | 286 | 0.0735 | 0.9217 | 0.4101 | 0.5348 |
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- | No log | 27.0 | 297 | 0.0742 | 0.9257 | 0.4136 | 0.5394 |
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- | No log | 28.0 | 308 | 0.0740 | 0.9124 | 0.405 | 0.5291 |
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- | No log | 29.0 | 319 | 0.0734 | 0.9124 | 0.405 | 0.5291 |
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- | No log | 30.0 | 330 | 0.0733 | 0.9124 | 0.405 | 0.5291 |
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  ### Framework versions
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- - Transformers 4.21.1
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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: 0.0733
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+ - Rouge2 Precision: 0.913
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+ - Rouge2 Recall: 0.4038
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+ - Rouge2 Fmeasure: 0.5257
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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 | 1.9724 | 0.0946 | 0.0257 | 0.0385 |
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+ | No log | 2.0 | 22 | 1.2952 | 0.0925 | 0.0263 | 0.039 |
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+ | No log | 3.0 | 33 | 0.8639 | 0.1083 | 0.0263 | 0.0409 |
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+ | No log | 4.0 | 44 | 0.5684 | 0.2212 | 0.0923 | 0.1248 |
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+ | No log | 5.0 | 55 | 0.3793 | 0.4327 | 0.1813 | 0.2445 |
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+ | No log | 6.0 | 66 | 0.2920 | 0.6667 | 0.3112 | 0.4008 |
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+ | No log | 7.0 | 77 | 0.2351 | 0.7234 | 0.309 | 0.409 |
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+ | No log | 8.0 | 88 | 0.2055 | 0.7374 | 0.3117 | 0.414 |
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+ | No log | 9.0 | 99 | 0.1787 | 0.7306 | 0.3002 | 0.4029 |
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+ | No log | 10.0 | 110 | 0.1540 | 0.7773 | 0.3267 | 0.4352 |
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+ | No log | 11.0 | 121 | 0.1406 | 0.7676 | 0.319 | 0.4246 |
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+ | No log | 12.0 | 132 | 0.1299 | 0.8478 | 0.3723 | 0.4887 |
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+ | No log | 13.0 | 143 | 0.1172 | 0.8202 | 0.3533 | 0.4675 |
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+ | No log | 14.0 | 154 | 0.1133 | 0.8543 | 0.3802 | 0.4976 |
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+ | No log | 15.0 | 165 | 0.1049 | 0.8543 | 0.3802 | 0.4976 |
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+ | No log | 16.0 | 176 | 0.0988 | 0.8252 | 0.3448 | 0.4603 |
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+ | No log | 17.0 | 187 | 0.0921 | 0.8702 | 0.385 | 0.5037 |
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+ | No log | 18.0 | 198 | 0.0877 | 0.8591 | 0.3684 | 0.4878 |
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+ | No log | 19.0 | 209 | 0.0878 | 0.8591 | 0.3654 | 0.4849 |
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+ | No log | 20.0 | 220 | 0.0849 | 0.8591 | 0.3654 | 0.4849 |
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+ | No log | 21.0 | 231 | 0.0806 | 0.882 | 0.3761 | 0.4974 |
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+ | No log | 22.0 | 242 | 0.0791 | 0.9232 | 0.4083 | 0.532 |
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+ | No log | 23.0 | 253 | 0.0794 | 0.8974 | 0.3869 | 0.5098 |
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+ | No log | 24.0 | 264 | 0.0773 | 0.9198 | 0.4104 | 0.5338 |
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+ | No log | 25.0 | 275 | 0.0744 | 0.9232 | 0.4083 | 0.532 |
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+ | No log | 26.0 | 286 | 0.0735 | 0.9232 | 0.4083 | 0.532 |
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+ | No log | 27.0 | 297 | 0.0742 | 0.9272 | 0.4115 | 0.5359 |
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+ | No log | 28.0 | 308 | 0.0740 | 0.913 | 0.4038 | 0.5257 |
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+ | No log | 29.0 | 319 | 0.0734 | 0.913 | 0.4038 | 0.5257 |
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+ | No log | 30.0 | 330 | 0.0733 | 0.913 | 0.4038 | 0.5257 |
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  ### Framework versions
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+ - Transformers 4.21.2
86
  - Pytorch 1.12.1+cu113
87
  - Datasets 2.4.0
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  - Tokenizers 0.12.1