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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: 0.9456
  • Accuracy: {'accuracy': 0.889}

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 0.6952 {'accuracy': 0.808}
0.4327 2.0 500 0.5493 {'accuracy': 0.857}
0.4327 3.0 750 0.5937 {'accuracy': 0.874}
0.212 4.0 1000 0.6253 {'accuracy': 0.891}
0.212 5.0 1250 0.7137 {'accuracy': 0.884}
0.0841 6.0 1500 0.7189 {'accuracy': 0.89}
0.0841 7.0 1750 0.8318 {'accuracy': 0.892}
0.0273 8.0 2000 0.9064 {'accuracy': 0.892}
0.0273 9.0 2250 0.9400 {'accuracy': 0.89}
0.0068 10.0 2500 0.9456 {'accuracy': 0.889}

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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