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elihoole/modern-bert-finetuned-query-classification

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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modern-bert-finetuned-query-classification

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

  • —Loss: 0.1256
  • —Accuracy: 0.9759
  • —F1: 0.9759
  • —Precision: 0.9763
  • —Recall: 0.9759

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: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
No log1.03150.14740.96480.96470.96490.9648
0.19652.06300.12260.97040.97040.97180.9704
0.19653.09450.11920.97410.97420.97570.9741
0.04264.012600.12500.97410.97410.97420.9741
0.00425.015750.12560.97590.97590.97630.9759

Framework versions

  • —Transformers 4.51.3
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.5.1
  • —Tokenizers 0.21.1