CoolFace
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ajrayman/auth_scale_binary

sourceHugging Facemitupdated 19d agoView on Hugging Face
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Model Card

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authscalebinary

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7318
  • Accuracy: 0.7011
  • Precision: 0.7102
  • Recall: 0.6783
  • F1: 0.6939
  • Auc: 0.7532

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: 32
  • evalbatchsize: 32
  • seed: 1234
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_ratio: 0.06
  • num_epochs: 8

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1Auc
No log1.01180.63260.67250.66120.70570.68280.7195
No log2.02360.62560.65260.59900.92020.72570.7527
No log3.03540.61950.68120.64020.82540.72110.7426
No log4.04720.73180.70110.71020.67830.69390.7532

Framework versions

  • Transformers 4.44.1
  • Pytorch 1.11.0
  • Datasets 2.12.0
  • Tokenizers 0.19.1