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ppak10/defect-classification-distilbert-baseline-10-epochs

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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defect-classification-distilbert-baseline-10-epochs

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2976
  • Accuracy: 0.8762

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: 512
  • evalbatchsize: 512
  • 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: 10

Training results

Training LossEpochStepValidation LossAccuracy
0.60081.010620.58670.7578
0.49862.021240.42980.8051
0.43223.031860.37860.8255
0.4584.042480.34250.8462
0.41435.053100.32740.8533
0.44436.063720.31530.8620
0.35087.074340.30760.8691
0.44898.084960.29890.8745
0.3649.095580.29740.8764
0.409110.0106200.29760.8762

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0