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Hate-Speech-Detection-mpnet-basev2

This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on the tweets_hate_speech_detection dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0849
  • Accuracy: 0.9750
  • F1: 0.8030

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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.1144 1.0 1599 0.0955 0.9693 0.7337
0.072 2.0 3198 0.0849 0.9750 0.8030
0.0458 3.0 4797 0.0841 0.9764 0.8011
0.0156 4.0 6396 0.1829 0.9689 0.7762
0.012 5.0 7995 0.1904 0.9745 0.7758
0.0157 6.0 9594 0.1622 0.9758 0.7914
0.0068 7.0 11193 0.1741 0.9736 0.8005

Framework versions

  • Transformers 4.26.1
  • Pytorch 2.0.1
  • Datasets 2.10.1
  • Tokenizers 0.13.3
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Dataset used to train Arvnd03/Hate-Speech-Detection-mpnet-basev2

Evaluation results