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Huyle2501/distilled-ModernBERT-to-DistilBERT-optuna

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

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distilled-ModernBERT-to-DistilBERT-optuna

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

  • —Loss: 0.8089
  • —Accuracy: 0.9374
  • —F1 Macro: 0.9416

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: 48
  • —evalbatchsize: 48
  • —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: 7

Training results

Training LossEpochStepValidation LossAccuracyF1 Macro
No log1.03182.34300.68740.6612
2.64812.06361.52260.84970.8474
2.64813.09541.10860.90900.9136
1.42084.012720.93100.92900.9330
0.93995.015900.85090.93420.9380
0.93996.019080.81960.93580.9398
0.79397.022260.80890.93740.9416

Framework versions

  • —Transformers 4.56.1
  • —Pytorch 2.8.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.0