---
library_name: transformers
license: mit
base_model: roberta-base-openai-detector
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-openai-detector-text2sql-approach-2
  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. -->

# roberta-base-openai-detector-text2sql-approach-2

This model is a fine-tuned version of [roberta-base-openai-detector](https://huggingface.co/roberta-base-openai-detector) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5172
- Accuracy: 0.79

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 57
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7594        | 1.0   | 57   | 0.7179          | 0.49     |
| 0.7011        | 2.0   | 114  | 0.6381          | 0.69     |
| 0.6694        | 3.0   | 171  | 0.6107          | 0.68     |
| 0.6091        | 4.0   | 228  | 0.5798          | 0.75     |
| 0.6088        | 5.0   | 285  | 0.5503          | 0.78     |
| 0.5765        | 6.0   | 342  | 0.5418          | 0.78     |
| 0.5857        | 7.0   | 399  | 0.5870          | 0.72     |
| 0.5793        | 8.0   | 456  | 0.5255          | 0.79     |
| 0.5507        | 9.0   | 513  | 0.5220          | 0.78     |
| 0.5404        | 10.0  | 570  | 0.5172          | 0.79     |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu118
- Datasets 3.6.0
- Tokenizers 0.21.1