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Aymeric-M/distilbert-base-uncased-lora-text-classification

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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distilbert-base-uncased-lora-text-classification

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: 1.0232
  • —Accuracy: {'accuracy': 0.889}

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: 0.001
  • —trainbatchsize: 4
  • —evalbatchsize: 4
  • —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
No log1.02500.4070{'accuracy': 0.882}
0.37372.05000.4423{'accuracy': 0.873}
0.37373.07500.8375{'accuracy': 0.868}
0.18514.010000.7292{'accuracy': 0.885}
0.18515.012500.8958{'accuracy': 0.895}
0.07416.015000.8747{'accuracy': 0.889}
0.07417.017500.9911{'accuracy': 0.888}
0.02678.020001.0290{'accuracy': 0.886}
0.02679.022501.0253{'accuracy': 0.89}
0.010210.025001.0232{'accuracy': 0.889}

Framework versions

  • —PEFT 0.13.2
  • —Transformers 4.46.3
  • —Pytorch 2.5.1+cu121
  • —Datasets 3.1.0
  • —Tokenizers 0.20.3