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buelfhood/conplag1_graphcodebert_ep30_bs16_lr1e-05_l512_s42_ppy_loss

sourceHugging Faceupdated 10mo agoView on Hugging Face
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Model Card

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conplag1graphcodebertep30bs16lr1e-05l512s42ppyloss

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

  • —Loss: 0.4643
  • —Accuracy: 0.8394
  • —Recall: 0.6316
  • —Precision: 0.75
  • —F1: 0.6857
  • —F Beta Score: 0.6638

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: 1e-05
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 30

Training results

Training LossEpochStepValidation LossAccuracyRecallPrecisionF1F Beta Score
0.67241.0400.62200.67880.76320.45310.56860.6304
0.57392.0800.50480.79560.68420.61900.650.6627
0.45483.01200.46430.83940.63160.750.68570.6638
0.3434.01600.62420.83210.47370.85710.61020.5493
0.44015.02000.48010.83210.65790.71430.68490.6743
0.33856.02400.48890.84670.63160.77420.69570.6695

Framework versions

  • —Transformers 4.51.3
  • —Pytorch 2.8.0+cu128
  • —Datasets 3.1.0
  • —Tokenizers 0.21.4