| --- |
| library_name: transformers |
| base_model: microsoft/codebert-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: ai-code-detector-finetuned |
| 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. --> |
|
|
| # ai-code-detector-finetuned |
|
|
| This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0001 |
| - Accuracy: 1.0 |
| - F1: 1.0 |
| - Tpr: 1.0 |
| - Tnr: 1.0 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 200 |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Tpr | Tnr | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---:| |
| | 0.0004 | 1.0 | 479 | 0.0136 | 0.9941 | 0.9942 | 0.9884 | 1.0 | |
| | 0.0001 | 2.0 | 958 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0001 | 3.0 | 1437 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0000 | 4.0 | 1916 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0000 | 5.0 | 2395 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.9.0 |
| - Pytorch 2.12.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
|
|
