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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: 0.9904
  • Accuracy: {'accuracy': 0.899}

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 0.5709 {'accuracy': 0.837}
0.4386 2.0 500 0.4510 {'accuracy': 0.871}
0.4386 3.0 750 0.6571 {'accuracy': 0.887}
0.1891 4.0 1000 0.6197 {'accuracy': 0.894}
0.1891 5.0 1250 0.7688 {'accuracy': 0.897}
0.0683 6.0 1500 0.8231 {'accuracy': 0.892}
0.0683 7.0 1750 0.8949 {'accuracy': 0.901}
0.0136 8.0 2000 0.9553 {'accuracy': 0.896}
0.0136 9.0 2250 1.0202 {'accuracy': 0.892}
0.0067 10.0 2500 0.9904 {'accuracy': 0.899}

Framework versions

  • PEFT 0.9.0
  • Transformers 4.39.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.12.0
  • Tokenizers 0.15.2
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