---
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-1
  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-1

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: 0.6802
- Accuracy: 0.58

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7355        | 1.0   | 57   | 0.7133          | 0.5      |
| 0.7256        | 2.0   | 114  | 0.6934          | 0.56     |
| 0.7062        | 3.0   | 171  | 0.6824          | 0.58     |
| 0.7048        | 4.0   | 228  | 0.6990          | 0.46     |
| 0.6976        | 5.0   | 285  | 0.7034          | 0.5      |
| 0.7104        | 6.0   | 342  | 0.7354          | 0.5      |
| 0.704         | 7.0   | 399  | 0.6808          | 0.58     |
| 0.6914        | 8.0   | 456  | 0.6776          | 0.6      |
| 0.6878        | 9.0   | 513  | 0.6849          | 0.54     |
| 0.6916        | 10.0  | 570  | 0.6802          | 0.58     |


### Framework versions

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