ai-code-detector-finetuned
This model is a fine-tuned version of 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 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2