metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-sql-classification-with_question
results: []
bert-base-uncased-finetuned-sql-classification-with_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: 0.6717
- Accuracy: 0.6
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.684 | 1.0 | 645 | 0.6930 | 0.5442 |
| 0.6908 | 2.0 | 1290 | 0.6892 | 0.5442 |
| 0.6929 | 3.0 | 1935 | 0.6999 | 0.5442 |
| 0.6887 | 4.0 | 2580 | 0.6903 | 0.5442 |
| 0.6898 | 5.0 | 3225 | 0.6899 | 0.5442 |
| 0.6887 | 6.0 | 3870 | 0.6916 | 0.5442 |
| 0.6819 | 7.0 | 4515 | 0.6835 | 0.5550 |
| 0.6742 | 8.0 | 5160 | 0.6576 | 0.6047 |
| 0.6546 | 9.0 | 5805 | 0.6477 | 0.6147 |
| 0.6478 | 10.0 | 6450 | 0.6717 | 0.6 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2