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ajrayman/Cheerfulness_binary

sourceHugging Facemitupdated 19d agoView on Hugging Face
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Model Card

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Cheerfulness_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: 0.6703
  • Accuracy: 0.6575
  • Precision: 0.6394
  • Recall: 0.7207
  • F1: 0.6776
  • Auc: 0.7037

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 log1.01180.66460.60400.56930.85040.6820.6888
No log2.02360.64000.64760.63050.71070.66820.7061
No log3.03540.67030.65750.63940.72070.67760.7037

Framework versions

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