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shgopal/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: 1.0848
  • —Accuracy: {'accuracy': 0.879}

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 OptimizerNames.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 log1.02500.4533{'accuracy': 0.862}
0.43362.05000.4592{'accuracy': 0.862}
0.43363.07500.6514{'accuracy': 0.872}
0.1914.010000.6980{'accuracy': 0.881}
0.1915.012500.8309{'accuracy': 0.891}
0.06356.015000.9549{'accuracy': 0.877}
0.06357.017501.0052{'accuracy': 0.878}
0.02318.020001.1275{'accuracy': 0.879}
0.02319.022501.0650{'accuracy': 0.879}
0.008310.025001.0848{'accuracy': 0.879}

Framework versions

  • —PEFT 0.14.0
  • —Transformers 4.49.0
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.4.1
  • —Tokenizers 0.21.1