---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- generator
metrics:
- accuracy
model-index:
- name: distilbert-sql-timeout-classifier-2024022722
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: generator
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9738276990185387
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-sql-timeout-classifier-2024022722

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1144
- Accuracy: 0.9738

## 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: 2e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.063         | 1.0   | 3064 | 0.1183          | 0.9684   |
| 0.041         | 2.0   | 6128 | 0.1046          | 0.9782   |
| 0.0265        | 3.0   | 9192 | 0.1144          | 0.9738   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2