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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- wikisql
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model-index:
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- name: EN_mt5-base_15_wikiSQL
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# EN_mt5-base_15_wikiSQL
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the wikisql dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0849
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- Rouge2 Precision: 0.8692
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- Rouge2 Recall: 0.7928
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- Rouge2 Fmeasure: 0.8234
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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- num_epochs: 15
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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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| 0.1534 | 1.0 | 4049 | 0.1157 | 0.8319 | 0.756 | 0.7858 |
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| 0.1204 | 2.0 | 8098 | 0.0980 | 0.8469 | 0.7706 | 0.8011 |
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| 0.1006 | 3.0 | 12147 | 0.0926 | 0.855 | 0.7775 | 0.8086 |
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| 0.0892 | 4.0 | 16196 | 0.0881 | 0.8579 | 0.7811 | 0.8119 |
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| 0.0809 | 5.0 | 20245 | 0.0857 | 0.8605 | 0.7839 | 0.8145 |
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| 0.0725 | 6.0 | 24294 | 0.0849 | 0.8643 | 0.787 | 0.8181 |
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| 0.0672 | 7.0 | 28343 | 0.0841 | 0.8662 | 0.7889 | 0.8199 |
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| 0.0628 | 8.0 | 32392 | 0.0847 | 0.8657 | 0.7895 | 0.82 |
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| 0.0589 | 9.0 | 36441 | 0.0835 | 0.8676 | 0.7909 | 0.8216 |
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| 0.0565 | 10.0 | 40490 | 0.0839 | 0.8685 | 0.7914 | 0.8223 |
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| 0.0532 | 11.0 | 44539 | 0.0837 | 0.8689 | 0.7925 | 0.8231 |
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| 0.051 | 12.0 | 48588 | 0.0844 | 0.8692 | 0.7927 | 0.8233 |
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| 0.0504 | 13.0 | 52637 | 0.0848 | 0.869 | 0.7924 | 0.8231 |
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| 0.0485 | 14.0 | 56686 | 0.0848 | 0.869 | 0.7928 | 0.8233 |
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| 0.0479 | 15.0 | 60735 | 0.0849 | 0.8692 | 0.7928 | 0.8234 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.7.dev0
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- Tokenizers 0.13.3
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