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distilbert-base-uncased__hate_speech_offensive__train-16-0

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

  • Loss: 1.2707
  • Accuracy: 0.517

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0943 1.0 10 1.1095 0.3
1.0602 2.0 20 1.1086 0.4
1.0159 3.0 30 1.1165 0.4
0.9027 4.0 40 1.1377 0.4
0.8364 5.0 50 1.0126 0.5
0.6653 6.0 60 0.9298 0.5
0.535 7.0 70 0.9555 0.5
0.3713 8.0 80 0.8543 0.4
0.1633 9.0 90 0.9876 0.4
0.1069 10.0 100 0.8383 0.6
0.0591 11.0 110 0.8056 0.6
0.0344 12.0 120 0.8915 0.6
0.0265 13.0 130 0.8722 0.6
0.0196 14.0 140 1.0064 0.6
0.0158 15.0 150 1.0479 0.6
0.0128 16.0 160 1.0723 0.6
0.0121 17.0 170 1.0758 0.6
0.0093 18.0 180 1.1236 0.6
0.0085 19.0 190 1.1480 0.6
0.0084 20.0 200 1.1651 0.6
0.0077 21.0 210 1.1832 0.6

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2
  • Tokenizers 0.10.3
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