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mcanoglu/salesforce-codet5p-220m-finetuned-defect-detection

sourceHugging Facebsd-3-clauseupdated 3y agoView on Hugging Face
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Salesforce-codet5p-220m-finetuned-defect-detection

This model is a fine-tuned version of Salesforce/codet5p-220m on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.5331
  • —Accuracy: 0.7289
  • —Roc Auc: 0.7292
  • —Precision: 0.7152
  • —Recall: 0.7395

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
0.69351.09960.57830.66890.66570.71970.5277
0.56942.019930.52790.70130.70260.67230.7580
0.48123.029890.50580.71810.71790.71290.7081
0.42354.039860.50880.72920.72910.72130.7261
0.36585.049800.53310.72890.72920.71520.7395

Framework versions

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