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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-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
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