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distilbert-hate_speech18

This model is a fine-tuned version of agvidit1/DistilledBert_HateSpeech_pretrain on the hate_speech18 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4684
  • Accuracy: 0.8588

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: 5.050180626898551e-06
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4404 1.0 240 0.4670 0.8533
0.4356 2.0 480 0.4642 0.8675
0.4303 3.0 720 0.4649 0.8748
0.4282 4.0 960 0.4694 0.8592
0.4273 5.0 1200 0.4638 0.8729
0.4256 6.0 1440 0.4651 0.8679
0.425 7.0 1680 0.4682 0.8560
0.4227 8.0 1920 0.4684 0.8588

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.1
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Model size
109M params
Tensor type
F32
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Finetuned from

Dataset used to train joseph10/distilbert-hate_speech18

Evaluation results