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kasparas12/distilbert-web3-classification

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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distilbert-web3-classification

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

  • Loss: 1.2908
  • Accuracy: 0.6672
  • F1: 0.6550

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: 64
  • seed: 42
  • optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracyF1
1.41621.013611.32940.57490.5271
1.18072.027221.22920.61630.5789
0.95743.040831.18570.64300.6207
0.73614.054441.18960.66880.6510
0.55485.068051.29080.66720.6550

Framework versions

  • Transformers 4.50.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1