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osabobo/distilbert-base-uncased-lora-text-classification

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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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: 0.8006
  • —Accuracy: {'accuracy': 0.893}

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
No log1.01250.2598{'accuracy': 0.896}
No log2.02500.3580{'accuracy': 0.888}
No log3.03750.4035{'accuracy': 0.885}
0.26224.05000.5133{'accuracy': 0.881}
0.26225.06250.6146{'accuracy': 0.886}
0.26226.07500.7576{'accuracy': 0.885}
0.26227.08750.7499{'accuracy': 0.885}
0.0458.010000.8082{'accuracy': 0.891}
0.0459.011250.8045{'accuracy': 0.89}
0.04510.012500.8006{'accuracy': 0.893}

Framework versions

  • —Transformers 4.42.3
  • —Pytorch 2.1.2
  • —Datasets 2.20.0
  • —Tokenizers 0.19.1