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PSchink/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: 0.9682
  • —Accuracy: {'accuracy': 0.89}

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 log1.02500.4717{'accuracy': 0.863}
0.43042.05000.4826{'accuracy': 0.865}
0.43043.07500.6937{'accuracy': 0.873}
0.17834.010000.6554{'accuracy': 0.896}
0.17835.012500.8139{'accuracy': 0.891}
0.05366.015000.7892{'accuracy': 0.896}
0.05367.017500.8994{'accuracy': 0.898}
0.01858.020000.9587{'accuracy': 0.892}
0.01859.022500.9562{'accuracy': 0.893}
0.002710.025000.9682{'accuracy': 0.89}

Framework versions

  • —PEFT 0.9.0
  • —Transformers 4.38.2
  • —Pytorch 2.2.1+cpu
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2