CoolFace
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ajrayman/psychopathy_binary

sourceHugging Facemitupdated 19d agoView on Hugging Face
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Model Card

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psychopathy_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: 0.9904
  • Accuracy: 0.6508
  • Precision: 0.7300
  • Recall: 0.48
  • F1: 0.5792
  • Auc: 0.7188

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 log1.01170.61480.64330.70180.50.58390.7171
No log2.02340.61550.64580.74480.4450.55710.7453
No log3.03510.69700.65830.64400.710.67540.7302
No log4.04680.83200.65710.73510.49250.58980.7264
0.49195.05850.99040.65080.73000.480.57920.7188

Framework versions

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