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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: 1.3644
  • Accuracy: {'accuracy': 0.858}

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 0.3793 {'accuracy': 0.856}
0.435 2.0 500 0.5190 {'accuracy': 0.858}
0.435 3.0 750 0.8326 {'accuracy': 0.857}
0.2005 4.0 1000 0.9137 {'accuracy': 0.856}
0.2005 5.0 1250 1.0362 {'accuracy': 0.862}
0.0827 6.0 1500 1.2331 {'accuracy': 0.852}
0.0827 7.0 1750 1.2110 {'accuracy': 0.856}
0.033 8.0 2000 1.2963 {'accuracy': 0.864}
0.033 9.0 2250 1.3438 {'accuracy': 0.863}
0.0128 10.0 2500 1.3644 {'accuracy': 0.858}

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.0
  • Pytorch 2.1.1+cpu
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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