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iremtasci/vera-model-v3

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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vera-model-v3

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.3031
  • —Accuracy: 0.9322
  • —F1: 0.9358
  • —Auc: 0.9922

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: 32
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 150
  • —num_epochs: 4
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyF1Auc
0.19761.04090.18760.93290.93490.9838
0.11742.08180.33730.91210.91840.9868
0.02463.012270.25360.94570.94770.9916
0.02004.016360.30500.9350.93810.9912

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2