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abandekar-dev/distilbert-onet

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face
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Model Card

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distilbert-onet

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: 0.6841
  • Accuracy: 0.7840
  • F1 Macro: 0.7159

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: 32
  • 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: 3

Training results

Training LossEpochStepValidation LossAccuracyF1 Macro
0.78991.09400.73870.74790.6602
0.58972.018800.69630.77550.6984
0.51413.028200.68410.78400.7159

Framework versions

  • Transformers 5.12.0
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2