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---
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
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