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bob-bob-bob-3/classification-hate-speech

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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classification-hate-speech

This model is a fine-tuned version of indolem/indobertweet-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3971
  • F1 macro: 0.3764
  • Weighted: 0.5676
  • Balanced accuracy: 0.5202

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: 5e-05
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 7

Training results

Training LossEpochStepValidation LossF1 macroWeightedBalanced accuracy
1.18811.0981.28810.36320.58180.4714
0.94422.01961.60410.35250.49770.5128
0.50453.02942.12710.32360.40880.5040
0.1114.03921.99560.36270.55790.5034
0.02795.04902.36650.37400.56270.5203
0.02036.05882.44680.36620.55120.5170
0.0067.06862.39710.37640.56760.5202

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1