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mcanoglu/bigcode-starcoderbase-1b-finetuned-defect-detection

sourceHugging Faceupdated 3y agoView on Hugging Face
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bigcode-starcoderbase-1b-finetuned-defect-detection

This model is a fine-tuned version of bigcode/starcoderbase-1b on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.9591
  • —Accuracy: 0.7666
  • —Roc Auc: 0.7662
  • —Precision: 0.7657
  • —Recall: 0.7523

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 LossAccuracyRoc AucPrecisionRecall
0.75961.09960.54060.68520.68970.62640.8813
0.48552.019930.46910.73770.73960.69540.8237
0.35473.029890.48320.74800.74790.74100.7441
0.24634.039860.59660.76280.76460.71960.8428
0.16335.049800.95910.76660.76620.76570.7523

Framework versions

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