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ARC4N3/roberta-hate-speech-olid

sourceHugging Faceupdated 3y agoView on Hugging Face
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experiment-model-roberta

This model is a fine-tuned version of facebook/roberta-hate-speech-dynabench-r4-target on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6733
  • Accuracy: 0.8538

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
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracy
0.32991.08840.34700.8453
0.30612.017680.34720.8546
0.27063.026520.39260.8583
0.17064.035360.54010.8495
0.14545.044200.67330.8538

Framework versions

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