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t5-text2sql

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PyTorch
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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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  1. README.md +15 -15
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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: 0.6322
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- - Rouge2 Precision: 0.7724
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- - Rouge2 Recall: 0.3399
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- - Rouge2 Fmeasure: 0.4581
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  ## Model description
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@@ -36,7 +36,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
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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 | 2.2055 | 0.0295 | 0.0079 | 0.0125 |
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- | No log | 2.0 | 22 | 1.3842 | 0.2474 | 0.12 | 0.1538 |
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- | No log | 3.0 | 33 | 0.9508 | 0.5971 | 0.3019 | 0.3938 |
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- | No log | 4.0 | 44 | 0.7835 | 0.7738 | 0.3436 | 0.4646 |
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- | No log | 5.0 | 55 | 0.7125 | 0.7635 | 0.3364 | 0.4561 |
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- | No log | 6.0 | 66 | 0.6709 | 0.7605 | 0.3407 | 0.4582 |
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- | No log | 7.0 | 77 | 0.6626 | 0.7868 | 0.3493 | 0.471 |
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- | No log | 8.0 | 88 | 0.6443 | 0.7684 | 0.3393 | 0.4578 |
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- | No log | 9.0 | 99 | 0.6320 | 0.7724 | 0.3399 | 0.4581 |
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- | No log | 10.0 | 110 | 0.6322 | 0.7724 | 0.3399 | 0.4581 |
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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: 0.4421
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+ - Rouge2 Precision: 0.8492
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+ - Rouge2 Recall: 0.37
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+ - Rouge2 Fmeasure: 0.5022
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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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 | 1.2891 | 0.3239 | 0.1492 | 0.198 |
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+ | No log | 2.0 | 22 | 0.7482 | 0.728 | 0.3254 | 0.4383 |
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+ | No log | 3.0 | 33 | 0.6458 | 0.7737 | 0.3366 | 0.459 |
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+ | No log | 4.0 | 44 | 0.5512 | 0.8333 | 0.356 | 0.4878 |
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+ | No log | 5.0 | 55 | 0.5363 | 0.8333 | 0.3622 | 0.4925 |
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+ | No log | 6.0 | 66 | 0.4863 | 0.8492 | 0.3702 | 0.5021 |
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+ | No log | 7.0 | 77 | 0.4715 | 0.8413 | 0.3663 | 0.4985 |
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+ | No log | 8.0 | 88 | 0.4629 | 0.8413 | 0.3663 | 0.4985 |
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+ | No log | 9.0 | 99 | 0.4397 | 0.8492 | 0.37 | 0.5022 |
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+ | No log | 10.0 | 110 | 0.4421 | 0.8492 | 0.37 | 0.5022 |
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  ### Framework versions