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nicolauduran45/deberta-v3-base4scientific-claim-verification

sourceHugging Facemitupdated 1y agoView on Hugging Face
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Model Card

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classifier

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: 0.9760
  • —F1-micro: 0.7354
  • —F1-macro: 0.7202
  • —F1-weighted: 0.7314
  • —Accuracy: 0.7354

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: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossF1-microF1-macroF1-weightedAccuracy
No log1.03860.75480.66150.65270.66270.6615
0.83842.07720.65180.71340.69810.70730.7134
0.60013.011580.67520.74190.73130.74080.7419
0.39264.015440.74890.73540.72320.73040.7354
0.39265.019300.97600.73540.72020.73140.7354

Framework versions

  • —Transformers 4.51.3
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.6.0
  • —Tokenizers 0.21.1