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4luc/codebert-code-clone-detector

sourceHugging Facemitupdated 2y agoView on Hugging Face
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codebert-code-clone-detector

This model is a fine-tuned version of microsoft/codebert-base on a Code Clone Benchmark dataset. See this github repository for more information. It achieves the following results on the evaluation set:

  • Loss: 0.3452
  • Accuracy: 0.9525
  • Precision: 0.9544
  • Recall: 0.9496
  • F1: 0.9520

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: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 15

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.34160.49330.17240.94170.98280.90480.9421
0.2210.97660.27680.9251.00.85710.9231
0.09291.46990.24690.95831.00.92060.9587
0.16961.941320.21420.950.95240.95240.9524
0.08182.431650.41420.9251.00.85710.9231
0.06762.911980.35390.93330.95080.92060.9355

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2