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MariaFGI/Modernbert-base-distilled-optuna-clinc

sourceHugging Faceapache-2.0updated 11mo agoView on Hugging Face
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Model Card

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Modernbert-base-distilled-optuna-clinc

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: 0.3763
  • —Accuracy: 0.9665

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: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 9
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
2.12811.09540.89300.9519
0.55052.019080.53840.9616
0.3043.028620.43930.9645
0.22844.038160.39990.9668
0.19025.047700.38590.9652
0.16656.057240.37630.9665

Framework versions

  • —Transformers 4.57.1
  • —Pytorch 2.8.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.1