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Hartunka/distilbert_km_100_v1_wnli

sourceHugging Faceupdated 1y agoView on Hugging Face
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distilbertkm100v1wnli

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

  • Loss: 0.7217
  • Accuracy: 0.4648

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 LossAccuracy
0.7251.030.72170.4648
0.70342.060.75180.2817
0.6963.090.74960.3239
0.68724.0120.75530.3803
0.68975.0150.78150.2535
0.68926.0180.82000.2535

Framework versions

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