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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: bert-base-uncased-finetuned-sql-classification-with_questionV2 |
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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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# bert-base-uncased-finetuned-sql-classification-with_questionV2 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4672 |
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- Accuracy: 0.9050 |
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- F1: 0.9172 |
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- Precision: 0.8744 |
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- Recall: 0.9645 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.5044 | 1.0 | 645 | 0.4149 | 0.8376 | 0.8617 | 0.8046 | 0.9275 | |
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| 0.3823 | 2.0 | 1290 | 0.3644 | 0.8535 | 0.8797 | 0.7965 | 0.9822 | |
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| 0.3289 | 3.0 | 1935 | 0.2915 | 0.8857 | 0.8998 | 0.8620 | 0.9410 | |
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| 0.2576 | 4.0 | 2580 | 0.3151 | 0.8860 | 0.9004 | 0.8602 | 0.9446 | |
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| 0.2224 | 5.0 | 3225 | 0.3157 | 0.9039 | 0.9155 | 0.8795 | 0.9545 | |
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| 0.1899 | 6.0 | 3870 | 0.3412 | 0.9016 | 0.9140 | 0.8731 | 0.9588 | |
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| 0.165 | 7.0 | 4515 | 0.3729 | 0.8973 | 0.9116 | 0.8591 | 0.9709 | |
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| 0.1265 | 8.0 | 5160 | 0.4119 | 0.9035 | 0.9162 | 0.8702 | 0.9673 | |
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| 0.1162 | 9.0 | 5805 | 0.4244 | 0.9066 | 0.9184 | 0.8766 | 0.9645 | |
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| 0.0995 | 10.0 | 6450 | 0.4672 | 0.9050 | 0.9172 | 0.8744 | 0.9645 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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