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Kuongan/CS221-deberta-base-finetuned-semeval-aug

sourceHugging Facemitupdated 2y agoView on Hugging Face
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CS221-deberta-base-finetuned-semeval-aug

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

  • —Loss: 0.2871
  • —F1: 0.8364
  • —Roc Auc: 0.8738
  • —Accuracy: 0.6387

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: 42
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 100
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossF1Roc AucAccuracy
0.27131.01390.38860.73100.80510.4228
0.29142.02780.33370.78490.84640.5248
0.22013.04170.30730.79950.85110.5501
0.14444.05560.30270.82750.87270.6007
0.09645.06950.28710.83640.87380.6387
0.05366.08340.30240.84320.87960.6612
0.0427.09730.29090.86310.89600.6920
0.03348.011120.29760.86750.90020.7037

Framework versions

  • —Transformers 4.47.1
  • —Pytorch 2.5.1+cu121
  • —Datasets 3.2.0
  • —Tokenizers 0.21.0