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afbudiman/distilled-optimized-indobert-classification

sourceHugging Faceupdated 4y agoView on Hugging Face
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Model Card

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distilled-optimized-indobert-classification

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

  • Loss: 0.7397
  • Accuracy: 0.9
  • F1: 0.8994

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: 4.315104717136378e-05
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 9

Training results

Training LossEpochStepValidation LossAccuracyF1
0.1281.06880.85350.89130.8917
0.14752.013760.91710.89130.8913
0.09973.020640.77990.89600.8951
0.07914.027520.71790.90320.9023
0.05775.034400.69080.90630.9055
0.04066.041280.76130.89920.8986
0.02757.048160.75020.89920.8989
0.0238.055040.74080.89760.8969
0.01699.061920.73970.90.8994

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.10.0+cu111
  • Datasets 2.1.0
  • Tokenizers 0.12.1