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cgallegoan
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t5-small-finetuned-acbsql

Text2Text Generation
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t5
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text-generation-inference
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update model card README.md

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  1. README.md +16 -16
README.md CHANGED
@@ -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-small](https://huggingface.co/t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1089
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- - Rouge2 Precision: 0.5759
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- - Rouge2 Recall: 0.2135
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- - Rouge2 Fmeasure: 0.306
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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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  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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- | No log | 1.0 | 79 | 0.3504 | 0.3762 | 0.1435 | 0.2038 |
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- | No log | 2.0 | 158 | 0.2444 | 0.4303 | 0.1587 | 0.2278 |
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- | No log | 3.0 | 237 | 0.1943 | 0.4982 | 0.1802 | 0.2612 |
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- | No log | 4.0 | 316 | 0.1622 | 0.5267 | 0.1882 | 0.2741 |
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- | No log | 5.0 | 395 | 0.1423 | 0.5596 | 0.2042 | 0.2946 |
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- | No log | 6.0 | 474 | 0.1284 | 0.5718 | 0.2118 | 0.3038 |
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- | 0.365 | 7.0 | 553 | 0.1199 | 0.574 | 0.2119 | 0.3042 |
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- | 0.365 | 8.0 | 632 | 0.1139 | 0.5761 | 0.2135 | 0.3059 |
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- | 0.365 | 9.0 | 711 | 0.1100 | 0.5757 | 0.2134 | 0.3057 |
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- | 0.365 | 10.0 | 790 | 0.1089 | 0.5759 | 0.2135 | 0.306 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0699
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+ - Rouge2 Precision: 0.6901
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+ - Rouge2 Recall: 0.2546
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+ - Rouge2 Fmeasure: 0.3639
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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+ | 0.7623 | 1.0 | 155 | 0.3883 | 0.3621 | 0.1411 | 0.1985 |
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+ | 0.3774 | 2.0 | 310 | 0.2040 | 0.5116 | 0.1845 | 0.2672 |
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+ | 0.2693 | 3.0 | 465 | 0.1461 | 0.5462 | 0.1958 | 0.2847 |
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+ | 0.2129 | 4.0 | 620 | 0.1147 | 0.5799 | 0.2135 | 0.3067 |
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+ | 0.1807 | 5.0 | 775 | 0.0948 | 0.6145 | 0.2264 | 0.3242 |
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+ | 0.1441 | 6.0 | 930 | 0.0847 | 0.6158 | 0.2298 | 0.3284 |
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+ | 0.1361 | 7.0 | 1085 | 0.0785 | 0.6389 | 0.2358 | 0.3371 |
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+ | 0.1268 | 8.0 | 1240 | 0.0733 | 0.6867 | 0.254 | 0.3628 |
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+ | 0.1259 | 9.0 | 1395 | 0.0709 | 0.6875 | 0.2538 | 0.3626 |
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+ | 0.1199 | 10.0 | 1550 | 0.0699 | 0.6901 | 0.2546 | 0.3639 |
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  ### Framework versions