mcanoglu/microsoft-codebert-base-finetuned-defect-detection

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microsoft-codebert-base-finetuned-defect-detection

This model is a fine-tuned version of microsoft/codebert-base on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.6197
• —Accuracy: 0.7382
• —Roc Auc: 0.7394
• —Precision: 0.7070
• —Recall: 0.7924

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: 8
• —evalbatchsize: 8
• —seed: 4711
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 5
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.37.2
• —Pytorch 2.2.0+cu121
• —Datasets 2.17.1
• —Tokenizers 0.15.2