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--- |
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base_model: TeeA/T5-Text2SQL-Bilingual |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: Text2SQL-Bilingual |
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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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# Text2SQL-Bilingual |
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This model is a fine-tuned version of [TeeA/T5-Text2SQL-Bilingual](https://huggingface.co/TeeA/T5-Text2SQL-Bilingual) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5456 |
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- Rouge1: 0.8237 |
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- Rouge2: 0.7136 |
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- Rougel: 0.8142 |
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- Rougelsum: 0.8137 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 4 |
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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: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 1.891 | 1.0 | 4389 | 1.7024 | 0.8289 | 0.7133 | 0.8163 | 0.8159 | |
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| 1.8333 | 2.0 | 8778 | 1.6619 | 0.8220 | 0.7113 | 0.8091 | 0.8089 | |
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| 1.7995 | 3.0 | 13167 | 1.6317 | 0.8213 | 0.7100 | 0.8102 | 0.8098 | |
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| 1.7632 | 4.0 | 17556 | 1.6076 | 0.8189 | 0.7074 | 0.8081 | 0.8076 | |
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| 1.7368 | 5.0 | 21945 | 1.5912 | 0.8219 | 0.7107 | 0.8106 | 0.8104 | |
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| 1.7121 | 6.0 | 26334 | 1.5715 | 0.8177 | 0.7052 | 0.8062 | 0.8060 | |
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| 1.7042 | 7.0 | 30723 | 1.5595 | 0.8210 | 0.7098 | 0.8104 | 0.8103 | |
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| 1.688 | 8.0 | 35112 | 1.5515 | 0.8220 | 0.7111 | 0.8118 | 0.8114 | |
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| 1.6647 | 9.0 | 39501 | 1.5482 | 0.8236 | 0.7122 | 0.8135 | 0.8131 | |
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| 1.6854 | 10.0 | 43890 | 1.5456 | 0.8237 | 0.7136 | 0.8142 | 0.8137 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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