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

sourceHugging Faceupdated 3y agoView on Hugging Face
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microsoft-codebert-base-finetuned-defect-cwe-group-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: 0.6195
  • —Accuracy: 0.7490
  • —Precision: 0.5725
  • —Recall: 0.5159

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

Training LossEpochStepValidation LossAccuracyPrecisionRecall
No log1.04620.60770.72880.63500.4460
0.72842.09250.54350.74850.64180.4633
0.52953.013870.59370.72090.52850.5098
0.42424.018500.60710.74000.55430.5354
0.35094.9923100.61950.74900.57250.5159

Framework versions

  • —Transformers 4.38.1
  • —Pytorch 2.2.1+cu121
  • —Datasets 2.17.1
  • —Tokenizers 0.15.2