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jamesLeeeeeee/code-search-net-tokenizer

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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code-search-net-tokenizer

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

  • Loss: 0.0619
  • Precision: 0.9355
  • Recall: 0.9502
  • F1: 0.9428
  • Accuracy: 0.9860

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: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 3

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.07491.017560.07040.89970.93030.91480.9805
0.03672.035120.06360.93780.94970.94370.9858
0.02433.052680.06190.93550.95020.94280.9860

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2