CoolFace
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philip1231/distil_low_lr

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

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distillowlr

This model is a fine-tuned version of distilbert/distilbert-base-uncased on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8611
  • Accuracy: 0.745

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: 1e-05
  • trainbatchsize: 64
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracy
No log1.0250.66220.5975
No log2.0500.60390.67
No log3.0750.56300.71
No log4.01000.56240.7075
No log5.01250.57490.7325
No log6.01500.58180.73
No log7.01750.60170.735
No log8.02000.64070.735
No log9.02250.67020.74
No log10.02500.69990.74
No log11.02750.72510.7325
No log12.03000.74720.735
No log13.03250.76470.745
No log14.03500.79620.74
No log15.03750.81200.7325
No log16.04000.82830.745
No log17.04250.83660.7425
No log18.04500.84810.745
No log19.04750.85880.7425
0.230220.05000.86110.745

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2