CoolFace
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JeffreyHuang/llm-selector

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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llm-selector

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: 1.7315
  • Accuracy: 0.5048

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: 2e-05
  • 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 log1.01181.89200.3714
No log2.02361.77530.5143
No log3.03541.76710.4952
No log4.04721.74410.5048
1.86655.05901.73150.5048
1.86656.07081.74130.5048
1.86657.08261.73780.4667
1.86658.09441.74260.4667
1.72549.010621.75130.4476
1.725410.011801.75130.4476

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1
  • Datasets 2.12.0
  • Tokenizers 0.13.3