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ajrayman/Orderliness_binary

sourceHugging Facemitupdated 19d agoView on Hugging Face
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Model Card

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Orderliness_binary

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: 0.9065
  • Accuracy: 0.6463
  • Precision: 0.6275
  • Recall: 0.7182
  • F1: 0.6698
  • Auc: 0.6949

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 log1.01180.64050.64130.61190.77060.68210.6834
No log2.02360.69500.58900.55150.94760.69720.7132
No log3.03540.71460.61640.57370.90270.70160.7210
No log4.04720.73900.65630.63560.73070.67980.7132
0.5485.05900.90650.64630.62750.71820.66980.6949

Framework versions

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