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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: 1.1367
  • Accuracy: {'accuracy': 0.881}

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 0.5355 {'accuracy': 0.834}
0.4237 2.0 500 0.5577 {'accuracy': 0.867}
0.4237 3.0 750 0.7444 {'accuracy': 0.868}
0.1861 4.0 1000 0.6896 {'accuracy': 0.884}
0.1861 5.0 1250 0.9201 {'accuracy': 0.881}
0.0388 6.0 1500 0.9153 {'accuracy': 0.894}
0.0388 7.0 1750 1.1074 {'accuracy': 0.877}
0.0076 8.0 2000 1.0988 {'accuracy': 0.883}
0.0076 9.0 2250 1.1251 {'accuracy': 0.878}
0.0029 10.0 2500 1.1367 {'accuracy': 0.881}

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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