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: 0.9731
  • Accuracy: {'accuracy': 0.891}

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
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 250 0.3222 {'accuracy': 0.895}
0.4357 2.0 500 0.4879 {'accuracy': 0.872}
0.4357 3.0 750 0.5919 {'accuracy': 0.895}
0.1751 4.0 1000 0.7484 {'accuracy': 0.885}
0.1751 5.0 1250 0.7662 {'accuracy': 0.892}
0.0628 6.0 1500 0.8518 {'accuracy': 0.88}
0.0628 7.0 1750 0.9047 {'accuracy': 0.894}
0.0186 8.0 2000 0.9434 {'accuracy': 0.894}
0.0186 9.0 2250 0.9598 {'accuracy': 0.895}
0.0083 10.0 2500 0.9731 {'accuracy': 0.891}

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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