---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-base-uncased-finetuned-sql-classification-with_questionV2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-base-uncased-finetuned-sql-classification-with_questionV2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4672
- Accuracy: 0.9050
- F1: 0.9172
- Precision: 0.8744
- Recall: 0.9645

## 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 | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5044        | 1.0   | 645  | 0.4149          | 0.8376   | 0.8617 | 0.8046    | 0.9275 |
| 0.3823        | 2.0   | 1290 | 0.3644          | 0.8535   | 0.8797 | 0.7965    | 0.9822 |
| 0.3289        | 3.0   | 1935 | 0.2915          | 0.8857   | 0.8998 | 0.8620    | 0.9410 |
| 0.2576        | 4.0   | 2580 | 0.3151          | 0.8860   | 0.9004 | 0.8602    | 0.9446 |
| 0.2224        | 5.0   | 3225 | 0.3157          | 0.9039   | 0.9155 | 0.8795    | 0.9545 |
| 0.1899        | 6.0   | 3870 | 0.3412          | 0.9016   | 0.9140 | 0.8731    | 0.9588 |
| 0.165         | 7.0   | 4515 | 0.3729          | 0.8973   | 0.9116 | 0.8591    | 0.9709 |
| 0.1265        | 8.0   | 5160 | 0.4119          | 0.9035   | 0.9162 | 0.8702    | 0.9673 |
| 0.1162        | 9.0   | 5805 | 0.4244          | 0.9066   | 0.9184 | 0.8766    | 0.9645 |
| 0.0995        | 10.0  | 6450 | 0.4672          | 0.9050   | 0.9172 | 0.8744    | 0.9645 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2