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---
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library_name: transformers
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license: mit
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base_model: roberta-base-openai-detector
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: roberta-base-openai-detector-text2sql-approach-2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# roberta-base-openai-detector-text2sql-approach-2
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This model is a fine-tuned version of [roberta-base-openai-detector](https://huggingface.co/roberta-base-openai-detector) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5172
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- Accuracy: 0.79
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 57
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.7594 | 1.0 | 57 | 0.7179 | 0.49 |
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| 0.7011 | 2.0 | 114 | 0.6381 | 0.69 |
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| 0.6694 | 3.0 | 171 | 0.6107 | 0.68 |
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| 0.6091 | 4.0 | 228 | 0.5798 | 0.75 |
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| 0.6088 | 5.0 | 285 | 0.5503 | 0.78 |
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| 0.5765 | 6.0 | 342 | 0.5418 | 0.78 |
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| 0.5857 | 7.0 | 399 | 0.5870 | 0.72 |
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| 0.5793 | 8.0 | 456 | 0.5255 | 0.79 |
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| 0.5507 | 9.0 | 513 | 0.5220 | 0.78 |
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| 0.5404 | 10.0 | 570 | 0.5172 | 0.79 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.7.0+cu118
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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