transformers safetensors distilbert text-classification generated_from_trainer dataset:generator base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert-base-uncased
datasets:
- generator
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-sql-timeout-classifier-with-features-4096-sql-normalized
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: generator
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.8906033190875284
      name: Accuracy
---

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# distilbert-sql-timeout-classifier-with-features-4096-sql-normalized

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: 0.5598
- Accuracy: 0.8906

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5057        | 1.0   | 1938 | 0.4010          | 0.8793   |
| 0.3304        | 2.0   | 3876 | 0.4271          | 0.8945   |
| 0.2143        | 3.0   | 5814 | 0.4978          | 0.8872   |
| 0.2079        | 4.0   | 7752 | 0.6021          | 0.8776   |
| 0.1329        | 5.0   | 9690 | 0.5598          | 0.8906   |


### Framework versions

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