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Hartunka/distilbert_km_100_v1_mrpc

sourceHugging Faceupdated 1y agoView on Hugging Face
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distilbertkm100v1mrpc

This model is a fine-tuned version of Hartunka/distilbert_km_100_v1 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6028
  • Accuracy: 0.7010
  • F1: 0.8146
  • Combined Score: 0.7578

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
0.62091.0150.61280.69850.80990.7542
0.57732.0300.60280.70100.81460.7578
0.52293.0450.61160.71080.81730.7641
0.4664.0600.64740.67650.76920.7229
0.36265.0750.68900.67160.76570.7187
0.23126.0900.92580.59800.68580.6419
0.14077.01051.02420.62990.72090.6754

Framework versions

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