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ALL_mt5-base_15_spider_15_wikiSQL_new

Text2Text Generation
Transformers
PyTorch
TensorBoard
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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update model card README.md

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@@ -13,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2909
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- - Rouge2 Precision: 0.6313
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- - Rouge2 Recall: 0.4304
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- - Rouge2 Fmeasure: 0.4825
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  ## Model description
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@@ -47,21 +47,21 @@ 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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- | 0.2246 | 1.0 | 1021 | 0.2285 | 0.5427 | 0.3561 | 0.4023 |
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- | 0.1399 | 2.0 | 2042 | 0.2178 | 0.5685 | 0.3784 | 0.4254 |
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- | 0.1064 | 3.0 | 3063 | 0.2239 | 0.5832 | 0.3955 | 0.443 |
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- | 0.0849 | 4.0 | 4084 | 0.2297 | 0.6109 | 0.4157 | 0.466 |
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- | 0.0725 | 5.0 | 5105 | 0.2445 | 0.6023 | 0.4067 | 0.4567 |
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- | 0.0614 | 6.0 | 6126 | 0.2444 | 0.607 | 0.4123 | 0.4621 |
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- | 0.053 | 7.0 | 7147 | 0.2522 | 0.6158 | 0.419 | 0.4694 |
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- | 0.0479 | 8.0 | 8168 | 0.2612 | 0.6187 | 0.4194 | 0.4706 |
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- | 0.043 | 9.0 | 9189 | 0.2636 | 0.6249 | 0.4268 | 0.4782 |
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- | 0.0402 | 10.0 | 10210 | 0.2697 | 0.6304 | 0.4296 | 0.4818 |
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- | 0.0368 | 11.0 | 11231 | 0.2770 | 0.6299 | 0.43 | 0.482 |
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- | 0.0348 | 12.0 | 12252 | 0.2836 | 0.6284 | 0.4274 | 0.4795 |
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- | 0.0329 | 13.0 | 13273 | 0.2879 | 0.6233 | 0.4242 | 0.4758 |
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- | 0.0324 | 14.0 | 14294 | 0.2913 | 0.6303 | 0.4296 | 0.4818 |
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- | 0.0313 | 15.0 | 15315 | 0.2909 | 0.6313 | 0.4304 | 0.4825 |
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  ### Framework versions
 
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0160
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+ - Rouge2 Precision: 0.9066
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+ - Rouge2 Recall: 0.6077
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+ - Rouge2 Fmeasure: 0.6916
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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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+ | 0.3243 | 1.0 | 1021 | 0.1423 | 0.6057 | 0.3898 | 0.4466 |
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+ | 0.1428 | 2.0 | 2042 | 0.0864 | 0.7175 | 0.4822 | 0.5453 |
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+ | 0.1071 | 3.0 | 3063 | 0.0644 | 0.7701 | 0.5183 | 0.5867 |
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+ | 0.0845 | 4.0 | 4084 | 0.0517 | 0.798 | 0.5398 | 0.611 |
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+ | 0.0723 | 5.0 | 5105 | 0.0417 | 0.8294 | 0.5584 | 0.6336 |
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+ | 0.0612 | 6.0 | 6126 | 0.0349 | 0.8411 | 0.5623 | 0.6394 |
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+ | 0.0528 | 7.0 | 7147 | 0.0302 | 0.853 | 0.5731 | 0.6514 |
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+ | 0.0475 | 8.0 | 8168 | 0.0254 | 0.8734 | 0.5842 | 0.6649 |
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+ | 0.0427 | 9.0 | 9189 | 0.0227 | 0.8855 | 0.5943 | 0.6757 |
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+ | 0.0398 | 10.0 | 10210 | 0.0208 | 0.8901 | 0.5965 | 0.6787 |
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+ | 0.0362 | 11.0 | 11231 | 0.0190 | 0.8943 | 0.5986 | 0.6815 |
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+ | 0.0343 | 12.0 | 12252 | 0.0178 | 0.9024 | 0.6045 | 0.6882 |
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+ | 0.0329 | 13.0 | 13273 | 0.0170 | 0.9075 | 0.6075 | 0.692 |
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+ | 0.0316 | 14.0 | 14294 | 0.0162 | 0.9081 | 0.6092 | 0.6935 |
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+ | 0.031 | 15.0 | 15315 | 0.0160 | 0.9066 | 0.6077 | 0.6916 |
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  ### Framework versions