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AurrieMartinez/distilbert-base-uncased-lora-text-classification

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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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: 0.9743
  • —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 log1.02500.5011{'accuracy': 0.849}
0.45072.05000.3976{'accuracy': 0.887}
0.45073.07500.5992{'accuracy': 0.891}
0.19284.010000.6172{'accuracy': 0.897}
0.19285.012500.7082{'accuracy': 0.89}
0.08276.015000.8177{'accuracy': 0.89}
0.08277.017500.8743{'accuracy': 0.886}
0.01278.020000.9673{'accuracy': 0.892}
0.01279.022500.9793{'accuracy': 0.89}
0.010310.025000.9743{'accuracy': 0.89}

Framework versions

  • —PEFT 0.11.1
  • —Transformers 4.41.1
  • —Pytorch 2.3.0+cu121
  • —Datasets 2.19.2
  • —Tokenizers 0.19.1