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Hartunka/distilbert_rand_10_v2_qqp

sourceHugging Faceupdated 1y agoView on Hugging Face
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distilbertrand10v2qqp

This model is a fine-tuned version of Hartunka/distilbert_rand_10_v2 on the GLUE QQP dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.3977
  • —Accuracy: 0.8198
  • —F1: 0.7526
  • —Combined Score: 0.7862

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: 5e-05
  • —trainbatchsize: 256
  • —evalbatchsize: 256
  • —seed: 10
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 50

Training results

Training LossEpochStepValidation LossAccuracyF1Combined Score
0.4781.014220.45050.78750.66390.7257
0.37052.028440.39770.81980.75260.7862
0.29633.042660.40500.82090.77020.7956
0.23844.056880.44760.82960.75330.7914
0.19315.071100.48680.83250.75660.7945
0.15716.085320.50580.83500.77610.8056
0.13057.099540.55940.83640.77730.8069

Framework versions

  • —Transformers 4.50.2
  • —Pytorch 2.2.1+cu121
  • —Datasets 2.18.0
  • —Tokenizers 0.21.1