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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: 0.8819
  • Accuracy: {'accuracy': 0.888}

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 0.3651 {'accuracy': 0.889}
0.4231 2.0 500 0.4402 {'accuracy': 0.879}
0.4231 3.0 750 0.6034 {'accuracy': 0.881}
0.1806 4.0 1000 0.7304 {'accuracy': 0.88}
0.1806 5.0 1250 0.6716 {'accuracy': 0.892}
0.0836 6.0 1500 0.6744 {'accuracy': 0.89}
0.0836 7.0 1750 0.7801 {'accuracy': 0.885}
0.0322 8.0 2000 0.8801 {'accuracy': 0.884}
0.0322 9.0 2250 0.8682 {'accuracy': 0.89}
0.0121 10.0 2500 0.8819 {'accuracy': 0.888}

Framework versions

  • PEFT 0.12.0
  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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