Sab286/ai-code-detector-finetuned

<!-- 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 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
• —trainbatchsize: 4
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 200
• —num_epochs: 5

Training results

Framework versions

• —Transformers 5.9.0
• —Pytorch 2.12.0+cu130
• —Datasets 4.8.5
• —Tokenizers 0.22.2