---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sql-classification-no_context
  results: []
---

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# distilbert-base-uncased-finetuned-sql-classification-no_context

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4138
- Accuracy: 0.8984

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4428        | 1.0   | 1290 | 0.3724          | 0.8360   |
| 0.3319        | 2.0   | 2580 | 0.3919          | 0.8744   |
| 0.3222        | 3.0   | 3870 | 0.3701          | 0.8911   |
| 0.2605        | 4.0   | 5160 | 0.3791          | 0.8911   |
| 0.2197        | 5.0   | 6450 | 0.4138          | 0.8984   |


### Framework versions

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