bert-base-uncased-finetuned-sql-classification-with_schema_question
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3313
- Accuracy: 0.9277
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6358 | 1.0 | 1036 | 0.5458 | 0.7165 |
| 0.4936 | 2.0 | 2072 | 0.4113 | 0.8881 |
| 0.4004 | 3.0 | 3108 | 0.4240 | 0.9026 |
| 0.3073 | 4.0 | 4144 | 0.3577 | 0.9122 |
| 0.2538 | 5.0 | 5180 | 0.3313 | 0.9277 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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Model tree for PatWang/bert-base-uncased-finetuned-sql-classification-with_schema_question
Base model
google-bert/bert-base-uncased