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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: 1.0886
  • Accuracy: {'accuracy': 0.885}

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 0.4321 {'accuracy': 0.87}
0.4477 2.0 500 0.4713 {'accuracy': 0.863}
0.4477 3.0 750 0.5655 {'accuracy': 0.877}
0.2184 4.0 1000 0.6685 {'accuracy': 0.872}
0.2184 5.0 1250 0.7549 {'accuracy': 0.889}
0.0709 6.0 1500 1.0147 {'accuracy': 0.885}
0.0709 7.0 1750 0.9756 {'accuracy': 0.878}
0.024 8.0 2000 1.0414 {'accuracy': 0.885}
0.024 9.0 2250 1.0876 {'accuracy': 0.886}
0.0053 10.0 2500 1.0886 {'accuracy': 0.885}

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.7
  • Tokenizers 0.15.0
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