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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: 1.0281
  • 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 0.3331 {'accuracy': 0.881}
0.4182 2.0 500 0.4217 {'accuracy': 0.89}
0.4182 3.0 750 0.5842 {'accuracy': 0.882}
0.2061 4.0 1000 0.6004 {'accuracy': 0.891}
0.2061 5.0 1250 0.7716 {'accuracy': 0.89}
0.0663 6.0 1500 0.9055 {'accuracy': 0.887}
0.0663 7.0 1750 1.0172 {'accuracy': 0.88}
0.0307 8.0 2000 1.0077 {'accuracy': 0.891}
0.0307 9.0 2250 0.9932 {'accuracy': 0.887}
0.0114 10.0 2500 1.0281 {'accuracy': 0.888}

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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