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Sube126/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 the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.0362
  • —Accuracy: {'accuracy': 0.866}

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 log1.02500.5633{'accuracy': 0.822}
0.44452.05000.5395{'accuracy': 0.85}
0.44453.07500.7314{'accuracy': 0.844}
0.31044.010000.6346{'accuracy': 0.867}
0.31045.012500.7909{'accuracy': 0.854}
0.18996.015000.8945{'accuracy': 0.872}
0.18997.017500.9758{'accuracy': 0.866}
0.08058.020001.0404{'accuracy': 0.865}
0.08059.022501.0483{'accuracy': 0.861}
0.058110.025001.0362{'accuracy': 0.866}

Framework versions

  • —PEFT 0.12.0
  • —Transformers 4.44.2
  • —Pytorch 2.4.1+cu121
  • —Datasets 3.0.0
  • —Tokenizers 0.19.1