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JohnsonManuel/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: 0.9540
  • —Accuracy: {'accuracy': 0.887}

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
No log1.02500.3484{'accuracy': 0.877}
0.41592.05000.5162{'accuracy': 0.865}
0.41593.07500.6527{'accuracy': 0.871}
0.1764.010000.6619{'accuracy': 0.889}
0.1765.012500.8626{'accuracy': 0.883}
0.06566.015000.8580{'accuracy': 0.883}
0.06567.017500.9169{'accuracy': 0.885}
0.028.020000.9219{'accuracy': 0.887}
0.029.022500.9387{'accuracy': 0.887}
0.001410.025000.9540{'accuracy': 0.887}

Framework versions

  • —PEFT 0.13.2
  • —Transformers 4.44.2
  • —Pytorch 2.4.1+cu121
  • —Datasets 3.0.1
  • —Tokenizers 0.19.1